Update Python packages

chestnut: alert when big model ready (#1947 )
egpu: alert when big model ready Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
2026-09-01 04:13:46 +08:00 · 2026-08-31 19:57:02 +00:00 · 2026-08-30 16:20:16 -04:00 · 2026-08-28 12:58:26 -04:00 · 2026-08-28 12:39:53 -04:00 · 2026-08-27 11:23:26 -04:00
59 changed files with 2699 additions and 872 deletions
@@ -8,13 +8,13 @@ on:
        required: true
        type: string
      target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
        required: true
        type: choice
        default: 'qcom'
        options:
          - qcom
-          - usbgpu
+          - chestnut
      hf_repo:
        description: 'Hugging Face dataset repository'
        required: false
@@ -59,7 +59,7 @@ jobs:
        id: get-json
        run: |
          cd docs/docs
-          PREFIX="driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_' || '' }}v"
+          PREFIX="driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_' || '' }}v"
          latest=$(ls ${PREFIX}*.json | sed -E "s/${PREFIX}([0-9]+)\.json/\1/" | sort -n | tail -1)
          next=$((latest+1))
          json_file="${PREFIX}${next}.json"
@@ -1,83 +0,0 @@
-name: Build default big model
-
-on:
-  workflow_dispatch:
-
-env:
-  HF_REPO: sunnypilot/sunnypilot_models_v1
-  HF_DEFAULTS_PATH: models/defaults/big
-
-jobs:
-  resolve_name:
-    runs-on: ubuntu-24.04
-    outputs:
-      model_name: ${{ steps.name.outputs.model_name }}
-      onnx_ref: ${{ steps.name.outputs.onnx_ref }}
-    steps:
-      - uses: actions/checkout@v4
-      - id: name
-        run: |
-          NAME=$(PYTHONPATH=${{ github.workspace }} python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
-          ONNX_REF=$(git log -1 --format='%H' -- openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx)
-          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
-          echo "onnx_ref=$ONNX_REF" >> $GITHUB_OUTPUT
-
-  build_model:
-    needs: resolve_name
-    uses: ./.github/workflows/sunnypilot-build-model.yaml
-    with:
-      upstream_branch: ${{ needs.resolve_name.outputs.onnx_ref }}
-      custom_name: ${{ needs.resolve_name.outputs.model_name }}
-      target_hardware: usbgpu
-    secrets: inherit
-
-  upload_defaults:
-    needs: [ resolve_name, build_model ]
-    runs-on: ubuntu-24.04
-    permissions:
-      id-token: write
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
-
-      - name: Install huggingface_hub
-        run: pip install --upgrade "huggingface_hub>=0.22.0"
-
-      - name: Download artifact name
-        uses: actions/download-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve_name.outputs.model_name }}
-          path: artifact_name
-
-      - name: Read artifact name
-        id: artifact
-        run: |
-          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
-          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
-
-      - name: Download model artifact
-        uses: actions/download-artifact@v4
-        with:
-          name: ${{ steps.artifact.outputs.artifact_name }}
-          path: output
-
-      - name: Upload to HF and update default_models.json
-        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
-          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
-        run: |
-          rm -f output/artifact_name.txt
-          export PYTHONPATH=$(pwd)
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ env.HF_DEFAULTS_PATH }}" \
-            --artifact-name "$ARTIFACT_NAME" \
-            --model-dir output \
-            --onnx-path "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" \
-            --onnx-ref "${{ needs.resolve_name.outputs.onnx_ref }}" \
-            --model-name "${{ needs.resolve_name.outputs.model_name }}" \
-            --tinygrad-ref "$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)" \
-            --run-number "${{ github.run_number }}"
@@ -0,0 +1,501 @@
+name: Build default models
+
+on:
+  workflow_dispatch:
+    inputs:
+      target:
+        description: 'Model target to build'
+        required: true
+        type: choice
+        options:
+          - small
+          - big
+          - dm
+  workflow_call:
+    inputs:
+      target:
+        description: 'Model target to build (small, big, or dm)'
+        required: true
+        type: string
+
+concurrency:
+  group: build-default-models-${{ inputs.target }}
+  cancel-in-progress: false
+
+env:
+  HF_REPO: sunnypilot/sunnypilot_models_v1
+
+jobs:
+  resolve:
+    runs-on: ubuntu-24.04
+    outputs:
+      model_name: ${{ steps.resolve.outputs.model_name }}
+      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
+      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
+      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
+      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - id: resolve
+        run: |
+          export PYTHONPATH=${{ github.workspace }}
+
+          if [ "${{ inputs.target }}" = "big" ]; then
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+            HF_DEFAULTS_PATH="models/defaults/big"
+          elif [ "${{ inputs.target }}" = "dm" ]; then
+            ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
+            HF_DEFAULTS_PATH="models/defaults/dm"
+            NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
+          else
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
+            HF_DEFAULTS_PATH="models/defaults/small"
+          fi
+
+          ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
+          TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
+          if [ -z "$TINYGRAD_REF" ]; then
+            echo "::error::Failed to resolve tinygrad ref"
+            exit 1
+          fi
+
+          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
+          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
+          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
+          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
+          echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
+
+  build_small_model:
+    needs: resolve
+    if: ${{ inputs.target == 'small' }}
+    runs-on: [self-hosted, tici]
+    env:
+      SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
+      SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull ONNX via LFS
+        run: git lfs pull -I "${{ env.SMALL_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile small model with stock compiler
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
+          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
+          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+
+          env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
+            --onnx ${{ github.workspace }}/${{ env.SMALL_ONNX }} \
+            --model-size $MODEL_SIZE \
+            --camera-resolutions $CAMERA_RES \
+            --frame-skip $FRAME_SKIP \
+            --output ${{ github.workspace }}/${{ env.SMALL_PKL }}
+
+      - name: Chunk small pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.SMALL_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
+
+      - name: Prepare output
+        env:
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/small_output"
+          PKL_BASE="driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload small model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/small_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          path: ${{ github.workspace }}/small_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  build_big_model:
+    needs: resolve
+    if: ${{ inputs.target == 'big' }}
+    runs-on: [self-hosted, chestnut]
+    env:
+      BIG_ONNX: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+      BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull big ONNX via LFS
+        run: git lfs pull -I "${{ env.BIG_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Wait for chestnut PCIe link
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          python3 -c "
+          import time
+          from openpilot.system.hardware.chestnut.flash import link_up
+          for i in range(10):
+              if link_up():
+                  print(f'PCIe link up after {i+1} attempt(s)')
+                  break
+              time.sleep(1)
+          else:
+              raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
+          "
+
+      - name: Compile big model with stock compiler
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
+          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
+          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
+
+          TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+
+          env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
+            --onnx ${{ github.workspace }}/${{ env.BIG_ONNX }} \
+            --model-size $MODEL_SIZE \
+            --camera-resolutions $CAMERA_RES \
+            --frame-skip $FRAME_SKIP \
+            --output ${{ github.workspace }}/${{ env.BIG_PKL }}
+
+      - name: Chunk big pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.BIG_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
+
+      - name: Prepare output
+        env:
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/big_output"
+          PKL_BASE="big_driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload big model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/big_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          path: ${{ github.workspace }}/big_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  upload_defaults:
+    needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
+    if: |
+      ${{
+        !cancelled() &&
+        (inputs.target == 'big' && needs.build_big_model.result == 'success' ||
+         inputs.target == 'small' && needs.build_small_model.result == 'success' ||
+         inputs.target == 'dm' && needs.build_dm_model.result == 'success')
+      }}
+    runs-on: ubuntu-24.04
+    permissions:
+      id-token: write
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Pull ONNX via LFS
+        run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
+
+      - name: Install huggingface_hub
+        run: pip install --upgrade "huggingface_hub>=0.22.0"
+
+      - name: Download artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          path: artifact_name
+
+      - name: Read artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        id: artifact
+        run: |
+          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
+          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
+
+      - name: Download model artifact
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.artifact.outputs.artifact_name }}
+          path: output
+
+      - name: Upload model to HF
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        env:
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
+          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
+        run: |
+          rm -f output/artifact_name.txt
+          export PYTHONPATH=$(pwd)
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "$ARTIFACT_NAME" \
+            --model-dir output \
+            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
+            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+      - name: Download DM artifact
+        if: ${{ inputs.target == 'dm' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output
+
+      - name: Generate DM metadata and upload to HF
+        if: ${{ inputs.target == 'dm' }}
+        env:
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
+        run: |
+          export PYTHONPATH=$(pwd)
+          python3 -c "
+          import json, hashlib
+          from pathlib import Path
+          from datetime import datetime, UTC
+
+          dm_dir = Path('dm_output')
+          manifest = list(dm_dir.glob('*.chunkmanifest'))
+          assert manifest, 'No chunkmanifest found'
+          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
+          num_chunks = int(manifest[0].read_text().strip())
+
+          chunks = []
+          for i in range(num_chunks):
+              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
+              chunks.append({
+                  'file_name': chunk.name,
+                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
+              })
+
+          digest = hashlib.sha256()
+          for c in chunks:
+              with open(dm_dir / c['file_name'], 'rb') as f:
+                  while block := f.read(1024*1024):
+                      digest.update(block)
+
+          metadata = {
+              'bundles': [{
+                  'short_name': 'DMMODEL',
+                  'display_name': '${{ needs.resolve.outputs.model_name }}',
+                  'ref': '${{ needs.resolve.outputs.onnx_ref }}',
+                  'runner': 'tinygrad',
+                  'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
+                  'models': [{
+                      'type': 'chunked',
+                      'artifact': {
+                          'file_name': pkl_name,
+                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
+                          'chunks': chunks
+                      }
+                  }]
+              }]
+          }
+          with open(dm_dir / 'metadata.json', 'w') as f:
+              json.dump(metadata, f, indent=2)
+          print('Generated DM metadata.json')
+          "
+
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "dm-model-${{ github.run_number }}" \
+            --model-dir dm_output \
+            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
+            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+  build_dm_model:
+    needs: resolve
+    if: ${{ inputs.target == 'dm' }}
+    runs-on: [self-hosted, tici]
+    env:
+      DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
+      DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull DM ONNX via LFS
+        run: git lfs pull -I "${{ env.DM_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile DM model
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+
+          taskset -c 7 env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
+            ${{ github.workspace }}/${{ env.DM_ONNX }} \
+            ${{ github.workspace }}/${{ env.DM_PKL }}
+
+      - name: Chunk DM pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked {pkl} into {len(targets)} chunks')
+          "
+
+      - name: Prepare DM output
+        run: |
+          mkdir -p dm_output
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
+
+      - name: Upload DM artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output/
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
@@ -30,7 +30,7 @@ on:
        type: boolean
        default: true
      target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
        required: false
        type: string
        default: 'qcom'
@@ -101,7 +101,7 @@ on:
        default: 'qcom'
        options:
          - qcom
-          - usbgpu
+          - chestnut
      hf_repo:
        description: 'Hugging Face dataset repository'
        required: false
@@ -109,7 +109,7 @@ on:
        default: 'sunnypilot/sunnypilot_models_v1'
 env:
  RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
-  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_v' || 'v' }}${{ inputs.json_version }}.json
+  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_v' || 'v' }}${{ inputs.json_version }}.json

 jobs:
  build_model:
@@ -0,0 +1,66 @@
+name: Download HF model chunks
+description: Resolve and download model chunks from HuggingFace in parallel
+
+inputs:
+  hf_repo:
+    description: HuggingFace dataset repo
+    required: true
+  models:
+    description: 'JSON array of {hf_path, onnx_hash, canonical} objects'
+    required: true
+  dest_dir:
+    description: Destination directory for downloaded chunks
+    required: true
+
+runs:
+  using: composite
+  steps:
+    - name: Download model chunks
+      shell: bash
+      env:
+        HF_REPO: ${{ inputs.hf_repo }}
+        MODELS_JSON: ${{ inputs.models }}
+        DEST_DIR: ${{ inputs.dest_dir }}
+      run: |
+        set -eo pipefail
+        DOWNLOAD_LIST=$(mktemp)
+
+        resolve_chunks() {
+          local HF_PATH="$1" ONNX_HASH="$2" CANONICAL="$3" DEST_DIR="$4"
+          local JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_PATH}/default_models.json"
+          local DEFAULTS BUNDLE ARTIFACT BASE_URL NUM_CHUNKS
+          DEFAULTS=$(curl -fsSL "$JSON_URL")
+          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
+          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
+
+          mkdir -p "$DEST_DIR"
+          while IFS= read -r CHUNK_NAME; do
+            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+' || true)
+            if [ -z "$CHUNK_IDX" ]; then
+              echo "::error::Failed to parse chunk index from: $CHUNK_NAME"
+              return 1
+            fi
+            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
+            printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}.chunk${CHUNK_IDX}" >> "$DOWNLOAD_LIST"
+          done < <(echo "$ARTIFACT" | jq -r '.chunks[].file_name')
+          echo "$NUM_CHUNKS" > "${DEST_DIR}/${CANONICAL}.chunkmanifest"
+        }
+
+        echo "$MODELS_JSON" | jq -c '.[]' | while IFS= read -r model; do
+          HF_PATH=$(echo "$model" | jq -r '.hf_path')
+          ONNX_HASH=$(echo "$model" | jq -r '.onnx_hash')
+          CANONICAL=$(echo "$model" | jq -r '.canonical')
+          resolve_chunks "$HF_PATH" "$ONNX_HASH" "$CANONICAL" "$DEST_DIR"
+        done
+
+        TOTAL=$(wc -l < "$DOWNLOAD_LIST")
+        echo "Downloading $TOTAL chunks with 8 parallel connections..."
+        xargs -P8 -d'\n' -I{} bash -c '
+          URL="${1%%	*}"
+          DEST="${1#*	}"
+          echo "Downloading $(basename "$DEST")"
+          curl -fsSL --retry 3 --retry-delay 5 -o "$DEST" "$URL"
+        ' _ {} < "$DOWNLOAD_LIST"
+        rm -f "$DOWNLOAD_LIST"
@@ -31,7 +31,7 @@ on:
        type: string
        default: ''
      target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
        required: false
        type: string
        default: 'qcom'
@@ -57,7 +57,7 @@ on:
        type: choice
        options:
          - qcom
-          - usbgpu
+          - chestnut
        default: 'qcom'


@@ -102,7 +102,7 @@ jobs:
          cat $GITHUB_OUTPUT
      - run: |
          cd ${{ github.workspace }}/openpilot/openpilot
-          if [ "${{ inputs.target_hardware }}" != "usbgpu" ]; then
+          if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
            git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx"
            rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx
          else
@@ -121,7 +121,7 @@ jobs:
          if-no-files-found: error

  build_model:
-    runs-on: [self-hosted, usbgpu]
+    runs-on: [self-hosted, chestnut]
    needs: get_model
    env:
      MODEL_NAME: ${{ inputs.custom_name || inputs.upstream_branch }} (${{ needs.get_model.outputs.model_date }})
@@ -185,10 +185,10 @@ jobs:
          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")

          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
-            echo "USBGPU build"
-            export USBGPU=1
-            TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+          if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
+            echo "CHESTNUT build"
+            export CHESTNUT=1
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
            OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
          else
            echo "QCOM build"
@@ -39,6 +39,8 @@ jobs:
      include_big_model: ${{ steps.strategy.outputs.include_big_model }}
    steps:
      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
      - name: Extract deploy strategy
        id: strategy
        run: |
@@ -96,6 +98,8 @@ jobs:
      }}
    steps:
      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
      - name: Wait for Tests
        uses: ./.github/workflows/wait-for-action # Path to where you place the action
        with:
@@ -119,6 +123,7 @@ jobs:
    steps:
      - uses: actions/checkout@v4
        with:
+          fetch-depth: 1
          submodules: recursive
          ref: ${{ env.SOURCE_BRANCH }}
          repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
@@ -165,7 +170,7 @@ jobs:
          scons -j1 cache_dir="$SCONS_CACHE" --minimal \
            openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
          echo "Building rest of sunnypilot"
-          /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
+          SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
          touch ${BUILD_DIR}/prebuilt
          if [[ "${{ runner.debug }}" == "1" ]]; then
            ls -la ${BUILD_DIR}
@@ -214,59 +219,174 @@ jobs:
    outputs:
      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
    env:
+      GH_REPO: ${{ github.repository }}
      HF_REPO: sunnypilot/sunnypilot_models_v1
      HF_DEFAULTS_PATH: models/defaults/big
    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ github.head_ref || github.ref_name }}
-
-      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
-
-      - name: Check HF defaults and build if needed
+      - name: Resolve ONNX hash and tinygrad ref via API
        id: resolve
        run: |
-          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
-          echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
-          echo "onnx_sha256=$ACTUAL_ONNX_HASH" >> $GITHUB_OUTPUT
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          ONNX_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "ONNX hash: $ONNX_HASH"
+          echo "onnx_sha256=$ONNX_HASH" >> $GITHUB_OUTPUT
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"

          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"

-          check_hash() {
+          check_defaults() {
            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
            [ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
          }

-          if check_hash; then
-            echo "HF defaults match repo ONNX"
-          else
-            echo "No matching model on HF — triggering build"
-            gh workflow run build-default-big-model.yaml --ref "${{ github.head_ref || github.ref_name }}"
-
-            echo "Waiting for build to start..."
-            sleep 120
-
-            RUN_ID=$(gh run list --workflow=build-default-big-model.yaml --branch="${{ github.head_ref || github.ref_name }}" --limit=1 --json databaseId --jq '.[0].databaseId')
-            if [ -z "$RUN_ID" ] || [ "$RUN_ID" = "null" ]; then
-              echo "::error::Failed to find build-default-big-model run"
-              exit 1
-            fi
-
-            echo "Waiting for run $RUN_ID..."
-            gh run watch "$RUN_ID"
-
-            CONCLUSION=$(gh run view "$RUN_ID" --json conclusion --jq '.conclusion')
-            if [ "$CONCLUSION" != "success" ]; then
-              echo "::error::build-default-big-model failed: $CONCLUSION"
-              exit 1
-            fi
-
-            if ! check_hash; then
-              echo "::error::HF defaults still don't match after build"
-              exit 1
-            fi
+          if check_defaults; then
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
+            exit 0
          fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
+
+          echo "Polling HF for big model availability..."
+          for i in $(seq 1 90); do
+            sleep 30
+            if check_defaults; then
+              echo "Big model available on HF after $((i * 30))s"
+              exit 0
+            fi
+            echo "Poll $i/90: not yet available"
+          done
+
+          echo "::error::Big model not available on HF after 45 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_small_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    outputs:
+      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/small
+    steps:
+      - name: Resolve ONNX hash and tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          DRIVING_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "Driving ONNX hash: $DRIVING_HASH"
+          echo "driving_onnx_sha256=$DRIVING_HASH" >> $GITHUB_OUTPUT
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DRIVING" ] && [ "$DRIVING" != "null" ] || return 1
+          }
+
+          if check_defaults; then
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
+
+          echo "Polling HF for model availability..."
+          for i in $(seq 1 60); do
+            sleep 30
+            if check_defaults; then
+              echo "Model available on HF after $((i * 30))s"
+              exit 0
+            fi
+            echo "Poll $i/60: not yet available"
+          done
+
+          echo "::error::Small driving model not available on HF after 30 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_dm_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    outputs:
+      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/dm
+    steps:
+      - name: Resolve ONNX hash and tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          DM_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "DM ONNX hash: $DM_HASH"
+          echo "dm_onnx_sha256=$DM_HASH" >> $GITHUB_OUTPUT
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DM" ] && [ "$DM" != "null" ] || return 1
+          }
+
+          if check_defaults; then
+            echo "HF defaults match DM ONNX hash and tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching DM model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
+
+          echo "Polling HF for DM model availability..."
+          for i in $(seq 1 60); do
+            sleep 30
+            if check_defaults; then
+              echo "DM model available on HF after $((i * 30))s"
+              exit 0
+            fi
+            echo "Poll $i/60: not yet available"
+          done
+
+          echo "::error::DM model not available on HF after 30 minutes"
+          exit 1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

@@ -278,23 +398,24 @@ jobs:

  publish:
    concurrency:
-      # We do a bit of a hack here to avoid canceling the publishing job if a new commit comes in while we're publishing by adding the sha to the group name.
-      # This means that if multiple commits come in while we're publishing, they will be queued up and publish one after the other.
-      # Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
    if: ${{
      always() && !cancelled() &&
      needs.build.result == 'success' &&
      needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
      (needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
      }}
-    needs: [ build, prepare_strategy, prepare_chestnut ]
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
    runs-on: ubuntu-24.04
    environment: ${{ needs.prepare_strategy.outputs.environment }}
    steps:
      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1

      - name: Download prebuilt artifact
        uses: actions/download-artifact@v4
@@ -306,43 +427,16 @@ jobs:
          mkdir -p ${{ env.OUTPUT_DIR }}
          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}

-      - name: Prepare chestnut output
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        run: |
-          mkdir -p "${{ github.workspace }}/chestnut_output"
-          tar xzf prebuilt.tar.gz -C "${{ github.workspace }}/chestnut_output"
-
-      - name: Download big model chunks from HF
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        env:
-          HF_REPO: sunnypilot/sunnypilot_models_v1
-          HF_DEFAULTS_PATH: models/defaults/big
-        run: |
-          ONNX_HASH="${{ needs.prepare_chestnut.outputs.onnx_sha256 }}"
-          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
-          DEFAULTS=$(curl -fsSL "$JSON_URL")
-          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
-
-          mkdir -p big_model_chunks
-          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
-          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
-
-          CANONICAL="big_driving_tinygrad.pkl"
-          echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
-            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
-            CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
-            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
-            echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
-            curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
-          done
-
-          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
-
-      - name: Inject big model into chestnut
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        run: |
-          cp big_model_chunks/* "${{ github.workspace }}/chestnut_output/openpilot/selfdrive/modeld/models/"
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
+        with:
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
+            ]

      - name: Configure Git
        run: |
@@ -364,22 +458,6 @@ jobs:
            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"

-      - name: Publish chestnut branch
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
-          CHESTNUT_DIR="${{ github.workspace }}/chestnut_output"
-
-          ${{ env.CI_DIR }}/publish.sh \
-            "${{ github.workspace }}" \
-            "$CHESTNUT_DIR" \
-            "$CHESTNUT_BRANCH" \
-            "${{ needs.prepare_strategy.outputs.version }}" \
-            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
-            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
-
      - name: Tag ${{ needs.prepare_strategy.outputs.environment }}
        if: ${{ needs.prepare_strategy.outputs.is_stable_branch == 'true' && (github.event_name != 'push' || !startsWith(github.ref, 'refs/tags/')) }}
        run: |
@@ -387,12 +465,77 @@ jobs:
            git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.prepare_strategy.outputs.build }}."
            git push -f origin ${TAG}

+  publish_chestnut:
+    concurrency:
+      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}-chestnut
+      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
+    if: ${{
+      always() && !cancelled() &&
+      needs.build.result == 'success' &&
+      needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
+      needs.prepare_chestnut.result == 'success' &&
+      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt'))
+      }}
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
+    runs-on: ubuntu-24.04
+    environment: ${{ needs.prepare_strategy.outputs.environment }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+
+      - name: Download prebuilt artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: prebuilt
+
+      - name: Untar prebuilt
+        run: |
+          mkdir -p ${{ env.OUTPUT_DIR }}
+          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
+
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
+        with:
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"},
+              {"hf_path": "models/defaults/big", "onnx_hash": "${{ needs.prepare_chestnut.outputs.onnx_sha256 }}", "canonical": "big_driving_tinygrad.pkl"}
+            ]
+
+      - name: Configure Git
+        run: |
+          git config --global user.email "github-actions[bot]@users.noreply.github.com"
+          git config --global user.name "github-actions[bot]"
+
+      - name: Publish chestnut branch
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
+
+          ${{ env.CI_DIR }}/publish.sh \
+            "${{ github.workspace }}" \
+            "${{ env.OUTPUT_DIR }}" \
+            "$CHESTNUT_BRANCH" \
+            "${{ needs.prepare_strategy.outputs.version }}" \
+            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
+            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
+
  notify:
    needs:
    - prepare_strategy
    - build
    - publish
+    - publish_chestnut
    - prepare_chestnut
+    - prepare_small_model
+    - prepare_dm_model
    runs-on: ubuntu-24.04
    if: ${{ (always() && !cancelled() && !failure())
      && needs.publish.result == 'success'
@@ -400,6 +543,8 @@ jobs:
      && (fromJSON(vars.DEV_FEEDBACK_NOTIFICATION_BRANCHES_V2)[github.head_ref || github.ref_name] != null) }}
    steps:
      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1

      - name: Prepare notification message
        id: message
@@ -131,6 +131,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
    downloaded @2;
    cached @3;
    failed @4;
+    verifying @5;
  }

  struct DownloadProgress {
@@ -352,6 +353,7 @@ struct OnroadEventSP @0xda96579883444c35 {
    speedLimitPending @22;
    e2eChime @23;
    laneChangeRoadEdge @24;
+    bigModelReady @25;
  }
 }

@@ -130,8 +130,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"UpdaterLastFetchTime", {PERSISTENT, TIME}},
    {"UptimeOffroad", {PERSISTENT, FLOAT, "0.0"}},
    {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
-    {"UsbGpuActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"UsbGpuLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
    {"Version", {PERSISTENT, STRING}},

    // --- sunnypilot params --- //
@@ -195,14 +195,16 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {

    // Model Manager params
    {"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, STRING}},
+    {"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}}, //TODO-SP: kept for migration, remove on next sync?
+    {"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
+    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
    {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
-    {"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
+    {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
    {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
    {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
-    {"ModelManager_LastSyncTime_USBGPU", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
+    {"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
    {"ModelManager_ModelsCache", {PERSISTENT | BACKUP, JSON}},
-    {"ModelManager_ModelsCache_USBGPU", {PERSISTENT | BACKUP, JSON}},
+    {"ModelManager_ModelsCache_Chestnut", {PERSISTENT | BACKUP, JSON}},

    // Neural Network Lateral Control
    {"NeuralNetworkLateralControl", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -245,6 +247,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {

    // mapd
    {"MapAdvisorySpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT}},
+    {"Mapd_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
    {"MapdVersion", {PERSISTENT, STRING}},
    {"MapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT, "0.0"}},
    {"NextMapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, JSON}},
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:845c40ff0d37612e8f2f482a36845744b5ae91ce2fcfc8117990d7d278b59820
+size 13079
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8a8c5fece2a1c7587feb41cbe04c6aee08e768ecd9b5d00da6af9832a4ccc842
-size 2034
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7409c53d7c72681c24982fd83b56ce70f80797c9c0f936d9296a5c18557ac472
-size 7279
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:58bd6155433f623b1f75d134bd8ca4745d9aa71f6767eb807cdbcf7deb3089a1
-size 10876
@@ -7,7 +7,7 @@ from openpilot.common.file_chunker import chunk_file, get_chunk_targets, get_exi
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE, DM_INPUT_SIZE
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, usbgpu_present, modeld_pkl_path
+from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, chestnut_present, modeld_pkl_path


 CAMERA_CONFIGS = [
@@ -36,18 +36,18 @@ else:
 tg_devices = { # which device to put jit inputs to at runtime
  'openpilot.selfdrive.modeld.modeld': {
    'default': {'WARP_DEV': tg_backend, 'QUEUE_DEV': tg_backend},
-    'usbgpu': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
+    'chestnut': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
  },
  'openpilot.selfdrive.modeld.dmonitoringmodeld': {
    'default': {'DEV': tg_backend}
  },
 }

-USBGPU = usbgpu_present()
-if USBGPU:
-  usbgpu_tg_flags = f'DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV={tg_backend} FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2'
+CHESTNUT = chestnut_present()
+if CHESTNUT:
+  chestnut_tg_flags = f'DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV={tg_backend} FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2'
  # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
-  usbgpu_lock = File("models/.usb_gpu.lock").abspath
+  chestnut_lock = File("models/.chestnut.lock").abspath

 def write_tg_devices(target, source, env):
  with open(str(target[0]), "w") as f:
@@ -73,44 +73,45 @@ compile_modeld_script = [
 model_w, model_h = MEDMODEL_INPUT_SIZE
 frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ

-for usbgpu in [False, True] if USBGPU else [False]:
-  target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
-  # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a USB GPU
-  file_prefix, cmd_flags = ('big_', usbgpu_tg_flags) if usbgpu else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
-  driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
-  camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
-  # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
-  taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
-  cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
-        f'--model-size {model_w}x{model_h} '
-        f'--camera-resolutions {camera_res_args} '
-        f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
-        f'--output {target_pkl_path} --frame-skip {frame_skip}')
-  onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
-  chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
-  def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
-    from openpilot.system.hardware.chestnut.flash import link_up
-    # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
-    for _ in range(10):
-      if link_up():
-        break
-      time.sleep(1)
-    else:
-      print("Chestnut not ready, skipping big model build")
-      return
-    if ret := env.Execute(command):
-      return ret
-    chunk_file(pkl, chunks)
-  def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
-    chunk_file(pkl, chunks)
-  actions = Action(do_compile, "  [USBGPU] $TARGET") if usbgpu else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
-  node = lenv.Command(
-    chunk_targets,
-    tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
-    actions,
-  )
-  if usbgpu:
-    lenv.SideEffect(usbgpu_lock, node)
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  for chestnut in [False, True] if CHESTNUT else [False]:
+    target_pkl_path = File(modeld_pkl_path(chestnut)).abspath
+    # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a chestnut
+    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
+    driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
+    camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
+    # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
+    taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
+    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
+          f'--model-size {model_w}x{model_h} '
+          f'--camera-resolutions {camera_res_args} '
+          f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
+          f'--output {target_pkl_path} --frame-skip {frame_skip}')
+    onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
+    chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
+    def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
+      from openpilot.system.hardware.chestnut.flash import link_up
+      # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
+      for _ in range(10):
+        if link_up():
+          break
+        time.sleep(1)
+      else:
+        print("Chestnut not ready, skipping big model build")
+        return
+      if ret := env.Execute(command):
+        return ret
+      chunk_file(pkl, chunks)
+    def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
+      chunk_file(pkl, chunks)
+    actions = Action(do_compile, "  [CHESTNUT] $TARGET") if chestnut else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
+    node = lenv.Command(
+      chunk_targets,
+      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
+      actions,
+    )
+    if chestnut:
+      lenv.SideEffect(chestnut_lock, node)

 # get model metadata
 fn = File(f"models/dmonitoring_model").abspath
@@ -142,4 +143,5 @@ def tg_compile(flags, model_name):
     Action(do_chunk, "  [CHUNK] $TARGET")],
  )

-tg_compile(tg_flags, 'dmonitoring_model')
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  tg_compile(tg_flags, 'dmonitoring_model')
@@ -29,7 +29,7 @@ class ModelState:
  output: np.ndarray

  def __init__(self, cam_w: int, cam_h: int):
-    self.DEV = get_tg_input_devices(PROCESS_NAME, usbgpu=False)['DEV']
+    self.DEV = get_tg_input_devices(PROCESS_NAME, chestnut=False)['DEV']
    with open(METADATA_PATH, 'rb') as f:
      model_metadata = pickle.load(f)
      self.input_shapes = model_metadata['input_shapes']
@@ -13,12 +13,12 @@ MODELS_DIR = Path(__file__).resolve().parent / 'models'
 TG_INPUT_DEVICES_PATH = MODELS_DIR / 'tg_input_devices.json'


-def get_tg_input_devices(process_name: str, usbgpu: bool):
+def get_tg_input_devices(process_name: str, chestnut: bool):
  with open(TG_INPUT_DEVICES_PATH) as f:
-    return json.load(f)[process_name]['default' if not usbgpu else 'usbgpu']
+    return json.load(f)[process_name]['default' if not chestnut else 'chestnut']

-def modeld_pkl_path(usbgpu: bool):
-  prefix = 'big_' if usbgpu else ''
+def modeld_pkl_path(chestnut: bool):
+  prefix = 'big_' if chestnut else ''
  return MODELS_DIR / f'{prefix}driving_tinygrad.pkl'

 def dump_oob(obj, f):
@@ -45,7 +45,7 @@ def load_oob(f):
      yield pb
  return pickle.load(io.BytesIO(opcodes), buffers=buffers())

-def usbgpu_present() -> bool:
+def chestnut_present() -> bool:
  for d in USB_DEVICES_PATH.glob("*"):
    try:
      usb_id = (int((d / "idVendor").read_text(), 16), int((d / "idProduct").read_text(), 16))
@@ -56,5 +56,5 @@ def usbgpu_present() -> bool:
      pass
  return False

-def usbgpu_compiled() -> bool:
-  return Path(get_manifest_path(modeld_pkl_path(usbgpu=True))).is_file()
+def chestnut_compiled() -> bool:
+  return Path(get_manifest_path(modeld_pkl_path(chestnut=True))).is_file()
@@ -1,7 +1,9 @@
 #!/usr/bin/env python3
+from collections.abc import Callable
+import ctypes
 from functools import cached_property
 import os
-os.environ['GMMU'] = '0' # for usbgpu fast loading, noop for qcom
+os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
 from tinygrad.tensor import Tensor
 from tinygrad.device import Device
 import struct
@@ -30,7 +32,7 @@ from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, WARP_IN
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_driving_model_data, fill_pose_msg, PublishState
 from openpilot.common.file_chunker import open_file_chunked
 from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
-from openpilot.selfdrive.modeld.helpers import usbgpu_present, usbgpu_compiled, modeld_pkl_path, get_tg_input_devices, load_oob
+from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, modeld_pkl_path, get_tg_input_devices, load_oob

 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
@@ -94,8 +96,10 @@ class ChestnutState:
    if self.big and "AMD" in Device._opened_devices and self.sends % 100 == 1:
      try:
        smu = Device["AMD"].iface.dev_impl.smu
+        metrics_t = smu.smu_mod.SmuMetricsExternal_t
        smu._send_msg(smu.smu_mod.PPSMC_MSG_TransferTableSmu2Dram, smu.smu_mod.TABLE_SMU_METRICS, timeout=100)
-        metrics = smu.read_table(smu.smu_mod.SmuMetricsExternal_t, smu.smu_mod.TABLE_SMU_METRICS).SmuMetrics
+        metrics_buf = bytearray(smu.adev.vram.view(smu.driver_table_paddr, ctypes.sizeof(metrics_t))[:])
+        metrics = metrics_t.from_buffer(metrics_buf).SmuMetrics
        self.metrics = {'tempC': metrics.AvgTemperature[smu.smu_mod.TEMP_HOTSPOT],
                        'memoryTempC': metrics.AvgTemperature[smu.smu_mod.TEMP_MEM],
                        'powerDrawW': metrics.AverageSocketPower,
@@ -141,18 +145,18 @@ class FrameMeta:
 class ModelState(ModelStateBase):
  prev_desire: np.ndarray  # for tracking the rising edge of the pulse

-  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool):
+  def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
    ModelStateBase.__init__(self)
-    input_devices = get_tg_input_devices(PROCESS_NAME, usbgpu)
+    input_devices = get_tg_input_devices(PROCESS_NAME, chestnut)
    self.WARP_DEV, self.QUEUE_DEV = input_devices['WARP_DEV'], input_devices['QUEUE_DEV']
-    jits = load_oob(open_file_chunked(modeld_pkl_path(usbgpu)))
+    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
    metadata = jits['metadata']
    self.input_shapes = metadata['input_shapes']
    self.vision_input_names = [k for k in self.input_shapes if 'img' in k]
    self.output_slices = metadata['output_slices']

    self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
-    self.usbgpu = usbgpu
+    self.chestnut = chestnut

    self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
@@ -168,7 +172,7 @@ class ModelState(ModelStateBase):
    return parsed_model_outputs

  def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
-          inputs: dict[str, np.ndarray]) -> dict[str, np.ndarray] | None:
+          inputs: dict[str, np.ndarray], after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray]:
    for key in bufs.keys():
      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
      yuv_size = self.frame_buf_params[key][3]
@@ -192,11 +196,11 @@ class ModelState(ModelStateBase):
    outs, = self.run_policy(
      **{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped
    )
+    if after_enqueue is not None:
+      after_enqueue()
    model_output = outs.numpy()[0]
-    if self.usbgpu and not np.all(np.isfinite(model_output)):
-      # TODO remove with prev_feat
-      cloudlog.error("model output not finite, dropping frame")
-      return None
+    if self.chestnut and not np.all(np.isfinite(model_output)):
+      raise RuntimeError("model output not finite")
    outputs_dict = self.parser.parse_outputs(self.slice_outputs(model_output, self.output_slices))
    self.npy['prev_feat'][:] = model_output[self.output_slices['hidden_state']]

@@ -218,12 +222,12 @@ class ModelState(ModelStateBase):
 def main(demo=False):
  cloudlog.warning("modeld init")

-  USBGPU = usbgpu_present() and usbgpu_compiled()
-  if USBGPU:
+  CHESTNUT = chestnut_present() and chestnut_compiled()
+  if CHESTNUT:
    os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
  params = Params()
-  params.put_bool("UsbGpuLoading", USBGPU)
-  params.remove("UsbGpuActive")
+  params.put_bool("ChestnutLoading", CHESTNUT)
+  params.remove("ChestnutActive")

  config_realtime_process(7, 54)

@@ -253,7 +257,7 @@ def main(demo=False):
  st = time.monotonic()
  cloudlog.warning("loading model")
  model = None
-  if USBGPU:
+  if CHESTNUT:
    big_model = None
    def load_big():
      nonlocal big_model
@@ -267,23 +271,23 @@ def main(demo=False):
    loader.start()
    loader.join(BIG_MODEL_TIMEOUT)
    model = big_model
-    params.put_bool("UsbGpuActive", model is not None)
+    params.put_bool("ChestnutActive", model is not None)

-  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or USBGPU else None
+  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or CHESTNUT else None
  if model is None:
    model = small_model
-  params.put_bool("UsbGpuLoading", False)
+  params.put_bool("ChestnutLoading", False)
  assert model is not None
  cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")

  # messaging
-  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if USBGPU else [])
+  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if CHESTNUT else [])
  pm = PubMaster(pub_socks)
  sm = SubMaster(["deviceState", "carState", "narrowRoadCameraState", "extrinsicsCalibration", "driverMonitoringState", "carControl", "lateralDelay"])

  publish_state = PublishState()
  params = Params()
-  chestnut_state = ChestnutState(pm, model.usbgpu) if USBGPU else None
+  chestnut_state = ChestnutState(pm, model.chestnut) if CHESTNUT else None

  # setup filter to track dropped frames
  frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_RUN_FREQ)
@@ -393,13 +397,15 @@ def main(demo=False):

    mt1 = time.perf_counter()
    try:
-      model_output = model.run(bufs, transforms, inputs)
+      send_chestnut = (chestnut_state is not None and
+                       run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0)
+      model_output = model.run(bufs, transforms, inputs, chestnut_state.send if send_chestnut else None)
    except Exception:
-      if not params.get_bool("UsbGpuActive"):
+      if not params.get_bool("ChestnutActive"):
        raise
      # fallback to small model
      cloudlog.exception("big model failed, fall back to small")
-      params.put_bool("UsbGpuActive", False)
+      params.put_bool("ChestnutActive", False)
      assert small_model is not None
      model = small_model
      if chestnut_state is not None:
@@ -419,7 +425,7 @@ def main(demo=False):
      fill_model_msg(modelv2_send, model_output, action,
                     publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                     frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, extrinsics_calibration_seen)
-      modelv2_send.modelV2.big = model.usbgpu
+      modelv2_send.modelV2.big = model.chestnut

      desire_state = modelv2_send.modelV2.meta.desireState
      l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
@@ -441,10 +447,6 @@ def main(demo=False):
      pm.send('modelDataV2SP', mdv2sp_send)
    last_vipc_frame_id = meta_main.frame_id

-    if chestnut_state is not None and run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
-      chestnut_state.send()
-
-
 if __name__ == "__main__":
  try:
    import argparse
@@ -195,17 +195,18 @@ class SelfdriveD(CruiseHelper):
      self.events.add(EventName.joystickDebug)
      self.startup_event = None

-    loading = self.params.get_bool("UsbGpuLoading")
+    loading = self.params.get_bool("ChestnutLoading")
    if self.big_model_loading and not loading:
      self.big_model_ready_t = time.monotonic()
+      self.events_sp.add(custom.OnroadEventSP.EventName.bigModelReady)
    self.big_model_loading = loading
    if self.big_model_loading:
      self.events.add(EventName.bigModelLoading)

-    big_active = self.params.get("UsbGpuActive")
-    usbgpu_present = self.sm['deviceState'].chestnutPresent
+    big_active = self.params.get("ChestnutActive")
+    chestnut_present = self.sm['deviceState'].chestnutPresent
    model_unavailable = big_active is True and self.sm.seen['modelV2'] and not self.sm.alive['modelV2']
-    big_failed = big_active is False or model_unavailable or (self.big_model_active and not usbgpu_present)
+    big_failed = big_active is False or model_unavailable or (self.big_model_active and not chestnut_present)
    if big_failed and not self.big_model_failed:
      self.events.add(EventName.bigModelFailed)
    self.big_model_failed = big_failed
@@ -575,7 +576,7 @@ class SelfdriveD(CruiseHelper):
    clear_event_types = set()
    if ET.WARNING not in self.state_machine.current_alert_types:
      clear_event_types.add(ET.WARNING)
-    if self.enabled or self.mads.clear_no_entry:
+    if self.enabled:
      clear_event_types.add(ET.NO_ENTRY)

    pers = LONGITUDINAL_PERSONALITY_MAP[self.personality]
@@ -168,9 +168,16 @@ class Sidebar(Widget, SidebarSP):
    # Home/Flag button
    flag_pressed = mouse_down and rl.check_collision_point_rec(mouse_pos, HOME_BTN)
    button_img = self._flag_img if ui_state.started else self._home_img
+    button_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
+    icon_opacity = 1.0
+
+    if gui_app.sunnypilot_ui():
+      button_img, button_pos, icon_opacity = SidebarSP._get_home_icon(self, button_img)

    tint = Colors.BUTTON_PRESSED if (ui_state.started and flag_pressed) else Colors.BUTTON_NORMAL
-    rl.draw_texture_ex(button_img, rl.Vector2(HOME_BTN.x, HOME_BTN.y), 0.0, 1.0, tint)
+    if icon_opacity < 1.0:
+      tint = rl.Color(tint[0], tint[1], tint[2], int(255 * icon_opacity))
+    rl.draw_texture_ex(button_img, button_pos, 0.0, 1.0, tint)

    # Microphone button
    if self._recording_audio:
@@ -9,7 +9,7 @@ from openpilot.system.ui.widgets.layouts import HBoxLayout
 from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
 from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
-from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.common.version import RELEASE_BRANCHES

 HEAD_BUTTON_FONT_SIZE = 40
@@ -139,8 +139,8 @@ class MiciHomeLayout(Widget):
    self._version_text = self._get_version_text()

    self._experimental_icon = IconWidget("icons_mici/experimental_mode.png", (48, 48))
-    self._egpu_icon = IconWidget("icons_mici/egpu_green.png", (50, 37))
-    self._egpu_icon_gray = IconWidget("icons_mici/egpu_gray.png", (50, 37))
+    self._chestnut_icon = IconWidget("icons_mici/chestnut_green.png", (68, 40))
+    self._chestnut_failed_icon = IconWidget("icons_mici/chestnut_orange.png", (68, 40))
    self._mic_icon = IconWidget("icons_mici/microphone.png", (32, 46))
    self._body_icon = IconWidget("icons_mici/body.png", (54, 37))

@@ -150,8 +150,8 @@ class MiciHomeLayout(Widget):
      IconWidget("icons_mici/settings.png", (48, 48), opacity=0.9),
      NetworkIcon(),
      self._experimental_icon,
-      self._egpu_icon,
-      self._egpu_icon_gray,
+      self._chestnut_icon,
+      self._chestnut_failed_icon,
      self._body_icon,
      self._mic_icon,
    ], spacing=18)
@@ -248,8 +248,11 @@ class MiciHomeLayout(Widget):

    # ***** Center-aligned bottom section icons *****
    self._experimental_icon.set_visible(ui_state.experimental_mode)
-    self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
-    self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
+    if gui_app.sunnypilot_ui():
+      self._set_chestnut_visibility()
+    else:
+      self._chestnut_icon.set_visible(ui_state.chestnut_state in (ChestnutState.READY, ChestnutState.LOADING, ChestnutState.ACTIVE))
+      self._chestnut_failed_icon.set_visible(ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
    self._mic_icon.set_visible(ui_state.recording_audio)
    self._body_icon.set_visible(bool(ui_state.is_body))

@@ -3,7 +3,7 @@ import pyray as rl
 from dataclasses import dataclass
 from openpilot.common.constants import CV
 from openpilot.selfdrive.ui.mici.onroad.torque_bar import TorqueBar
-from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus
+from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus, ChestnutState
 from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.lib.text_measure import measure_text_cached
@@ -107,8 +107,7 @@ class HudRenderer(Widget):
    self.speed: float = 0.0
    self.v_ego_cluster_seen: bool = False
    self._engaged: bool = False
-    self._small_model_engaged: bool = False
-    self._egpu_fade_time: float = 0
+    self._chestnut_fade_time: float = 0

    self._can_draw_top_icons = True
    self._show_wheel_critical = False
@@ -124,17 +123,15 @@ class HudRenderer(Widget):
    self._txt_wheel: rl.Texture = gui_app.texture('icons_mici/wheel.png', 50, 50)
    self._txt_wheel_critical: rl.Texture = gui_app.texture('icons_mici/wheel_critical.png', 50, 50)
    self._txt_exclamation_point: rl.Texture = gui_app.texture('icons_mici/exclamation_point.png', 9, 44)
-    self._txt_egpu: rl.Texture = gui_app.texture('icons_mici/egpu.png', 60, 44)
-    self._txt_egpu_green: rl.Texture = gui_app.texture('icons_mici/egpu_green.png', 60, 44)
-    self._txt_egpu_orange: rl.Texture = gui_app.texture('icons_mici/egpu_orange.png', 60, 44)
-    self._txt_egpu_crossed: rl.Texture = gui_app.texture('icons_mici/egpu_crossed.png', 60, 52)
-    self._egpu_icon: rl.Texture | None = None
-
+    self._txt_chestnut: rl.Texture = gui_app.texture('icons_mici/chestnut.png', 60, 44)
+    self._txt_chestnut_green: rl.Texture = gui_app.texture('icons_mici/chestnut_green.png', 60, 44)
+    self._txt_chestnut_orange: rl.Texture = gui_app.texture('icons_mici/chestnut_orange.png', 75, 44)
+    self._chestnut_icon: rl.Texture | None = None
    self._wheel_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
    self._wheel_y_filter = FirstOrderFilter(0, 0.1, 1 / gui_app.target_fps)

    self._set_speed_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)
-    self._egpu_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)
+    self._chestnut_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)

  def set_wheel_critical_icon(self, critical: bool):
    """Set the wheel icon to critical or normal state."""
@@ -165,13 +162,10 @@ class HudRenderer(Widget):
      controls_state.deprecated.vCruise if v_cruise_cluster == 0.0 else v_cruise_cluster
    )
    engaged = sm['selfdriveState'].enabled
-    if (engaged and not self._engaged and not ui_state.usbgpu_loading and ui_state.usbgpu_active is not True and
-        ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame):
-      self._small_model_engaged = True
-    if engaged != self._engaged:
-      self._egpu_fade_time = rl.get_time() if engaged else 0
    if (set_speed != self.set_speed and engaged) or (engaged and not self._engaged):
      self._set_speed_changed_time = rl.get_time()
+    if engaged != self._engaged:
+      self._chestnut_fade_time = rl.get_time() if engaged else 0
    self._engaged = engaged
    self.set_speed = set_speed
    self.is_cruise_set = 0 < self.set_speed < SET_SPEED_NA
@@ -191,8 +185,7 @@ class HudRenderer(Widget):
    if self.is_cruise_set:
      self._draw_set_speed(rect)

-    if ui_state.usbgpu and ui_state.usbgpu_compiled:
-      self._draw_model_source(rect)
+    self._draw_model_source(rect)

    self._draw_steering_wheel(rect)

@@ -200,30 +193,24 @@ class HudRenderer(Widget):
    if ui_state.sm.recv_frame['selfdriveState'] < ui_state.started_frame:
      return

-    big_failed = (ui_state.usbgpu_active is False or not ui_state.sm['deviceState'].chestnutPresent or
-                  (ui_state.usbgpu_active is True and ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame and
-                   not ui_state.sm.alive['modelV2']) or
-                  (ui_state.usbgpu_active is None and ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame))
-    self._small_model_engaged &= big_failed
-    loading = ui_state.usbgpu_loading or (ui_state.usbgpu_active is None and not big_failed)
+    loading = ui_state.chestnut_state == ChestnutState.LOADING
    if loading:
-      pulse = 0.5 - 0.5 * math.cos(rl.get_time() * 6.0)
-      icon = self._txt_egpu
-      opacity = 0.35 + 0.65 * pulse
-    elif self._small_model_engaged:
-      icon = self._txt_egpu_crossed
-      opacity = 0.65
-    elif big_failed:
-      icon = self._txt_egpu_orange
+      icon = self._txt_chestnut
+      opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+    elif ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED):
+      icon = self._txt_chestnut_orange
+      opacity = 1.0
+    elif ui_state.chestnut_state == ChestnutState.ACTIVE:
+      icon = self._txt_chestnut_green
      opacity = 1.0
    else:
-      icon = self._txt_egpu_green
-      opacity = 1.0
+      return

-    if icon is not self._egpu_icon:
-      self._egpu_fade_time = rl.get_time()
-      self._egpu_icon = icon
-    alpha = self._egpu_alpha_filter.update(loading or 0 < rl.get_time() - self._egpu_fade_time < SET_SPEED_PERSISTENCE)
+    if icon is not self._chestnut_icon:
+      self._chestnut_fade_time = rl.get_time()
+      self._chestnut_icon = icon
+    visible = loading or rl.get_time() - self._chestnut_fade_time < SET_SPEED_PERSISTENCE
+    alpha = self._chestnut_alpha_filter.update(visible)
    if alpha < 1e-2:
      return

@@ -10,9 +10,10 @@ import time
 import pyray as rl

 from openpilot.cereal import custom
-from openpilot.sunnypilot.models.default_model import get_default_model
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_selected_bundle, resolve_bundle_by_ref
 from openpilot.common.constants import CV
 from openpilot.selfdrive.ui.ui_state import device, ui_state
+from openpilot.selfdrive.ui.sunnypilot.model_info import big_model_state, bundles_for_source, carrying_model, default_model_name, queued_name
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.widgets import DialogResult, Widget
@@ -36,7 +37,10 @@ class ModelsLayout(Widget):
    super().__init__()
    self.model_manager = None
    self.model_dialog = None
+    self._selection_source = None
    self._downloading = False
+    self._verifying = False
+    self._last_note = None
    self.last_cache_calc_time = 0

    self._initialize_items()
@@ -48,17 +52,24 @@ class ModelsLayout(Widget):
    self._scroller = Scroller(self.items, line_separator=True, spacing=0)

  def _initialize_items(self):
-    self.current_model_item = ListItemSP(
-      title=tr("Current Model"),
+    self.small_model_item = ListItemSP(
+      title=tr("Small Model"),
      description="",
      action_item=ScrollingButtonAction(tr("SELECT")),
-      callback=self._handle_current_model_clicked
+      callback=lambda: self._open_source_dialog("qcom")
+    )
+
+    self.big_model_item = ListItemSP(
+      title=tr("Big Model"),
+      action_item=ScrollingButtonAction(tr("SELECT")),
+      callback=lambda: self._open_source_dialog("chestnut")
    )

    self.download_item = download_status_item(lambda: tr("Download") if self._downloading else tr("Model Status"))

    self.refresh_item = button_item(tr("Refresh Model List"), tr("REFRESH"), "",
                                    lambda: (ui_state.params.put("ModelManager_LastSyncTime", 0),
+                                             ui_state.params.put("ModelManager_LastSyncTime_Chestnut", 0),
                                             gui_app.push_widget(alert_dialog(tr("Fetching Latest Models")))))

    self.clear_cache_item = ListItemSP(
@@ -68,7 +79,9 @@ class ModelsLayout(Widget):
      callback=self._clear_cache
    )

-    self.cancel_download_item = button_item(tr("Cancel Download"), tr("Cancel"), "", lambda: ui_state.params.remove("ModelManager_DownloadIndex"))
+    self.cancel_download_item = button_item(lambda: tr("Cancel Verification") if self._verifying else tr("Cancel Download"),
+                                            tr("Cancel"), "",
+                                            lambda: ui_state.params.remove("ModelManager_DownloadRef"))

    self.lane_turn_value_control = option_item_sp(tr("Adjust Lane Turn Speed"), "LaneTurnValue", 500, 2000,
                                                  tr("Set the maximum speed for lane turn desires. Default is 19 mph."),
@@ -93,7 +106,7 @@ class ModelsLayout(Widget):
                                        1, None, True, "", style.BUTTON_ACTION_WIDTH, None, True,
                                        lambda v: f"{v / 100:.2f} m")

-    self.items = [self.current_model_item, self.cancel_download_item, self.download_item, self.refresh_item, self.clear_cache_item,
+    self.items = [self.small_model_item, self.big_model_item, self.cancel_download_item, self.download_item, self.refresh_item, self.clear_cache_item,
                  self.lane_turn_desire_toggle, self.lane_turn_value_control, self.lagd_toggle, self.delay_control, self.camera_offset]

  def _update_lagd_description(self, lagd_toggle: bool):
@@ -107,16 +120,16 @@ class ModelsLayout(Widget):
      desc += f"<br>{tr('Actuator Delay:')} {cp:.2f} s + {tr('Software Delay:')} {sw:.2f} s = {tr('Total Delay:')} {cp + sw:.2f} s"
    self.lagd_toggle.set_description(desc)

-  def _is_downloading(self):
-    return (self.model_manager and self.model_manager.selectedBundle and
-            self.model_manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloading)
-
  @staticmethod
  def calculate_cache_size():
    cache_size = 0.0
    if os.path.exists(CUSTOM_MODEL_PATH):
-      cache_size = sum(os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file)) for file in os.listdir(CUSTOM_MODEL_PATH)) / (1024**2)
-    return cache_size
+      for file in os.listdir(CUSTOM_MODEL_PATH):
+        try:
+          cache_size += os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file))
+        except OSError:
+          continue
+    return cache_size / (1024**2)

  def _clear_cache(self):
    def _callback(response):
@@ -129,36 +142,90 @@ class ModelsLayout(Widget):
    gui_app.push_widget(dialog)

  def _handle_bundle_download_progress(self):
-    self.download_item.set_visible(False)
    self.cancel_download_item.set_visible(False)
    self._downloading = False
-
-    if not self.model_manager or (not self.model_manager.selectedBundle and not self.model_manager.activeBundle):
-      return
-
-    bundle = self.model_manager.selectedBundle if self._is_downloading() or (
-      self.model_manager.selectedBundle and self.model_manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.failed
-    ) else self.model_manager.activeBundle
-    if not bundle:
-      return
-
-    self.cancel_download_item.set_visible(bool(self.model_manager.selectedBundle) and ui_state.params.get("ModelManager_DownloadIndex") is not None)
+    self._verifying = False
+    self.download_item.set_visible(True)

    if (current_time := time.monotonic()) - self.last_cache_calc_time > 0.5:
      self.last_cache_calc_time = current_time
      self.clear_cache_item.action_item.set_value(f"{self.calculate_cache_size():.2f} MB")

+    bundle = self.model_manager.selectedBundle if self.model_manager else None
+    progresses = [model.artifact.downloadProgress for model in bundle.models if model.artifact.fileName] if bundle else []
+    if not progresses or bundle.status not in (custom.ModelManagerSP.DownloadStatus.downloading,
+                                               custom.ModelManagerSP.DownloadStatus.failed):
+      self.download_item.action_item.update(name="", segments=self._slot_segments())
+      return
+
+    self.cancel_download_item.set_visible(ui_state.params.get("ModelManager_DownloadRef") is not None)
    if bundle.status == custom.ModelManagerSP.DownloadStatus.downloading:
      device._reset_interactive_timeout()

-    # every bundle is a single chunked artifact now
-    progresses = [model.artifact.downloadProgress for model in bundle.models if model.artifact.fileName]
-    if not progresses:
-      return
-
-    self.download_item.set_visible(True)
-    self.download_item.action_item.update(**self._download_row_state(progresses, bundle.internalName))
+    state = self._download_row_state(progresses, bundle.internalName)
+    if queued := queued_name(bundle.ref):
+      state["name"] += f"  |  {queued} {tr('queued')}"
+    self.download_item.action_item.update(**state)
    self._downloading = self.download_item.action_item.downloading
+    ds = custom.ModelManagerSP.DownloadStatus
+    self._verifying = any(getattr(p.status, 'raw', p.status) == ds.verifying for p in progresses)
+
+  def _slot_segments(self):
+    """small and big slots side by side; green marks the slot whose pick is actually
+    driving (runner-matched, so a failed Default big greens neither slot), an empty
+    slot shows its default."""
+    big_state = big_model_state()
+    carry_source, carry_internal, _ = carrying_model()
+    segments = []
+    for source, label in (("qcom", tr("small")), ("chestnut", tr("big"))):
+      if segments:
+        segments.append(("|", rl.GRAY, None, None))
+      bundle = get_selected_bundle(ui_state.params, source)
+      name = bundle.internalName if bundle else default_model_name(source)
+      color = ON_COLOR if (source == carry_source and name == carry_internal) else rl.LIGHTGRAY
+      name = "● " + name
+      if source == "chestnut":
+        if big_state == 'failed':
+          color = rl.RED
+        elif big_state == 'loading':
+          color = rl.GOLD
+      segments.append((label, rl.GRAY, None, None))
+      segments.append((name, color, None, None))
+    return segments
+
+  @staticmethod
+  def _set_item_note(item, text):
+    # a description renders only while shown; hide before clearing or the
+    # empty description keeps its visible state
+    if text:
+      item.set_description(text)
+      item.show_description(True)
+    else:
+      item.show_description(False)
+      item.set_description("")
+
+  def _status_note(self) -> str:
+    """The failover story for the Model Status row. One-way big -> small, and the
+    fallback is runner-matched: a Default big can only fall back to the Default
+    small (stock modeld), a custom big has no automatic fallback yet."""
+    if not ui_state.chestnut_present:
+      return ""
+    big_bundle = get_selected_bundle(ui_state.params, "chestnut")
+    big_name = big_bundle.internalName if big_bundle else default_model_name("chestnut")
+    big_is_default = big_bundle is None
+    fallback_name = default_model_name("qcom")
+    state = big_model_state()
+    if state == 'failed':
+      if big_is_default:
+        return tr("Big model unavailable, {} is driving until the next drive.").format(fallback_name)
+      return tr("Big model unavailable until the next drive.")
+    if state == 'loading':
+      if big_is_default:
+        return tr("{} drives until the big model is ready.").format(fallback_name)
+      return tr("Getting the big model ready.")
+    if big_is_default:
+      return tr("{} will drive. If it fails during a drive, {} takes over until the next drive.").format(big_name, fallback_name)
+    return tr("{} will drive when the chestnut is ready.").format(big_name)

  @staticmethod
  def _download_row_state(progresses, name: str) -> dict:
@@ -171,6 +238,8 @@ class ModelsLayout(Widget):
    if ds.failed in statuses:
      # close.png is authored black and a tint cannot lift it, hence close2
      return {"name": name, "status_text": tr("download failed"), "text_color": rl.RED, "icon": "icons/close2.png"}
+    if ds.verifying in statuses:
+      return {"name": name, "downloading": True, "progress": progress, "status_text": tr("verifying")}
    if ds.downloading in statuses:
      return {"name": name, "downloading": True, "progress": progress}
    if statuses <= {ds.downloaded, ds.cached}:
@@ -180,50 +249,71 @@ class ModelsLayout(Widget):

  def _on_model_selected(self, result):
    if result != DialogResult.CONFIRM:
+      self.model_dialog = None
      return
    selected_ref = self.model_dialog.selection_ref
-    if selected_ref == "Default":
-      ui_state.params.remove("ModelManager_ActiveBundle")
-    elif selected_bundle := next((bundle for bundle in self.model_manager.availableBundles if bundle.ref == selected_ref), None):
-      ui_state.params.put("ModelManager_DownloadIndex", selected_bundle.index)
    self.model_dialog = None
+    if selected_ref == "Default":
+      if self._selection_source in ACTIVE_BUNDLE_KEYS:
+        ui_state.params.remove(ACTIVE_BUNDLE_KEYS[self._selection_source])
+      return
+    if selected_bundle := self._resolve_selected_bundle(selected_ref):
+      ui_state.params.put("ModelManager_DownloadRef", selected_bundle.ref)
+
+  def _resolve_selected_bundle(self, ref):
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    resolved = resolve_bundle_by_ref(ref, source_bundles)
+    return resolved[0] if resolved else None

  @staticmethod
  def _bundle_to_node(bundle):
    return TreeNode(bundle.ref, {'display_name': bundle.displayName, 'short_name': bundle.internalName})

-  def _get_folders(self, favorites):
-    bundles = self.model_manager.availableBundles
+  def _get_folders(self, favorites, bundles):
    folders = {}
    for bundle in bundles:
      folders.setdefault(next((ov_ride.value for ov_ride in bundle.overrides if ov_ride.key == "folder"), ""), []).append(bundle)

-    folders_list = [TreeFolder("", [TreeNode("Default", {'display_name': f"{get_default_model()} (Default)",
-                                                         'short_name': "Default"})])]
+    folders_list = []
    for folder, folder_bundles in sorted(folders.items(), key=lambda x: max((bundle.index for bundle in x[1]), default=-1), reverse=True):
      folder_bundles.sort(key=lambda bundle: bundle.index, reverse=True)
      name = folder + (f" - (Updated: {m.group(1)})" if folder_bundles and (m := re.search(r'\(([^)]*)\)[^(]*$', folder_bundles[0].displayName)) else "")
      folders_list.append(TreeFolder(name, [self._bundle_to_node(bundle) for bundle in folder_bundles]))

    if favorites and (fav_bundles := [bundle for bundle in bundles if bundle.ref in favorites]):
-      folders_list.insert(1, TreeFolder("Favorites", [self._bundle_to_node(bundle) for bundle in fav_bundles]))
+      folders_list.insert(0, TreeFolder("Favorites", [self._bundle_to_node(bundle) for bundle in fav_bundles]))
    return folders_list

-  def _handle_current_model_clicked(self):
+  def _open_source_dialog(self, source):
+    self._selection_source = source
    favs = ui_state.params.get("ModelManager_Favs")
    favorites = set(favs.split(';')) if favs else set()
-    folders_list = self._get_folders(favorites)
-
-    active_ref = self.model_manager.activeBundle.ref if self.model_manager.activeBundle else "Default"
-    self.model_dialog = TreeOptionDialog(tr("Select a Model"), folders_list, active_ref, "ModelManager_Favs",
-                                         get_folders_fn=self._get_folders, on_exit=self._on_model_selected)
+    folders_list = self._source_folders(favorites, source)
+    if not folders_list:
+      gui_app.push_widget(alert_dialog(tr("No models are available for this hardware yet. Connect to the internet and refresh the model list.")))
+      return
+    self.model_dialog = TreeOptionDialog(tr("Select a Model"), folders_list, self._slot_active_ref(source), "ModelManager_Favs",
+                                         get_folders_fn=lambda favs: self._source_folders(favs, source), on_exit=self._on_model_selected)
    gui_app.push_widget(self.model_dialog)

+  def _source_folders(self, favorites, source):
+    bundles = bundles_for_source(source)
+    if not bundles:
+      return []
+    folders_list = [TreeFolder("", [TreeNode("Default", {'display_name': default_model_name(source)})])]
+    folders_list.extend(self._get_folders(favorites, bundles))
+    return folders_list
+
+  @staticmethod
+  def _slot_active_ref(source: str) -> str:
+    bundle = get_selected_bundle(ui_state.params, source)
+    return bundle.ref if bundle else "Default"
+
  def _update_state(self):
    advanced_controls: bool = ui_state.params.get_bool("ShowAdvancedControls")
    turn_desire: bool = ui_state.params.get_bool("LaneTurnDesire")
    live_delay: bool = ui_state.params.get_bool("LagdToggle")
-    camera_offset: bool = ui_state.params.get("ModelManager_ActiveBundle") is not None
+    camera_offset: bool = ui_state.active_bundle is not None

    self.lane_turn_desire_toggle.action_item.set_state(turn_desire)
    self.lane_turn_value_control.set_visible(turn_desire and advanced_controls)
@@ -237,19 +327,27 @@ class ModelsLayout(Widget):
    self._update_lagd_description(live_delay)
    self.model_manager = ui_state.sm["modelManagerSP"]
    self._handle_bundle_download_progress()
-    default_label = f"{get_default_model()} (Default)"
-    active_name = self.model_manager.activeBundle.displayName if self.model_manager and self.model_manager.activeBundle.ref else default_label
-    self.current_model_item.action_item.set_value(active_name)

-    if not ui_state.is_offroad():
-      self.current_model_item.action_item.set_enabled(False)
-      self.current_model_item.set_description(tr("Only available when vehicle is off, or always offroad mode is on"))
-    else:
-      self.current_model_item.action_item.set_enabled(True)
-      self.current_model_item.set_description("")
+    carry_source, _, carry_display = carrying_model()
+    for item, item_source in ((self.small_model_item, "qcom"), (self.big_model_item, "chestnut")):
+      bundle = get_selected_bundle(ui_state.params, item_source)
+      name = bundle.displayName if bundle else default_model_name(item_source)
+      color = ON_COLOR if (item_source == carry_source and name == carry_display) else style.ITEM_TEXT_VALUE_COLOR
+      item.action_item.set_value(name, color)
+
+    note = self._status_note()
+    if note != self._last_note:
+      self._last_note = note
+      self._set_item_note(self.download_item, note)
+
+    offroad = ui_state.is_offroad()
+    self.small_model_item.action_item.set_enabled(offroad)
+    self.big_model_item.action_item.set_enabled(offroad)
+    self.small_model_item.set_description("" if offroad else tr("Only available when vehicle is off, or always offroad mode is on"))

  def _render(self, rect):
    self._scroller.render(rect)

  def show_event(self):
    self._scroller.show_event()
+    self._last_note = None  # re-expand the failover note every time the page opens
@@ -8,7 +8,6 @@ import datetime
 import os
 import platform
 import requests
-import shutil
 import threading
 from pathlib import Path
 from time import monotonic
@@ -75,22 +74,12 @@ class OSMLayout(Widget):
  def _update_map_size(self):
    threading.Thread(target=self.calculate_size, daemon=True).start()

-  def _do_delete_maps(self):
-    if MAP_PATH.exists():
-      shutil.rmtree(MAP_PATH)
-
-    for param in ("OsmDownloadedDate", "OsmLocal", "OsmLocationName", "OsmLocationTitle", "OsmStateName", "OsmStateTitle"):
-      ui_state.params.remove(param)
-
+  def _on_confirm_delete_maps(self):
+    ui_state.params.put_bool("Mapd_ClearCache", True)
    self._delete_maps_btn.action_item.set_enabled(True)
    self._delete_maps_btn.action_item.set_text(tr("DELETE"))
    self._update_map_size()

-  def _on_confirm_delete_maps(self):
-    self._delete_maps_btn.action_item.set_enabled(False)
-    self._delete_maps_btn.action_item.set_text("DELETING...")
-    threading.Thread(target=self._do_delete_maps).start()
-
  def _delete_maps(self):
    self._show_confirm(tr("This will delete ALL downloaded maps\n\nAre you sure you want to delete all maps?"),
                       tr("Yes, delete all maps"), self._on_confirm_delete_maps)
@@ -4,11 +4,14 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
+import math
+
 import pyray as rl
 import time
 from dataclasses import dataclass
-from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
+from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.lib.multilang import tr_noop


@@ -18,6 +21,9 @@ METRIC_MARGIN = 30
 METRIC_START_Y = 300
 HOME_BTN = rl.Rectangle(60, 860, 180, 180)

+CHESTNUT_ICON_WIDTH = 180
+CHESTNUT_ICON_HEIGHT = 133
+

 # Color scheme
 class Colors:
@@ -53,6 +59,9 @@ class MetricData:
 class SidebarSP:
  def __init__(self):
    self._sunnylink_status = MetricData(tr_noop("SUNNYLINK"), tr_noop("OFFLINE"), Colors.WARNING)
+    self._chestnut_green_img = gui_app.texture("icons_mici/chestnut_green.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._chestnut_default_img = gui_app.texture("icons_mici/chestnut.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._chestnut_orange_img = gui_app.texture("icons_mici/chestnut_orange.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)

  def _update_sunnylink_status(self):
    if not ui_state.params.get_bool("SunnylinkEnabled"):
@@ -78,6 +87,24 @@ class SidebarSP:

    self._sunnylink_status.update(tr_noop("SUNNYLINK"), status, color)

+  def _get_home_icon(self, default_img: rl.Texture) -> tuple[rl.Texture, rl.Vector2, float]:
+    default_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
+    state = ui_state.chestnut_state
+    if state == ChestnutState.DISCONNECTED:
+      return default_img, default_pos, 1.0
+
+    if state == ChestnutState.LOADING:
+      icon = self._chestnut_default_img
+      opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+    elif state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED):
+      icon, opacity = self._chestnut_orange_img, 1.0
+    else:
+      icon, opacity = self._chestnut_green_img, 1.0
+
+    x = HOME_BTN.x + (HOME_BTN.width - icon.width) / 2
+    y = HOME_BTN.y + (HOME_BTN.height - icon.height) / 2
+    return icon, rl.Vector2(x, y), opacity
+
  def _draw_metrics_w_sunnylink(self, rect: rl.Rectangle, _temp, _panda, _connect):
    metrics = [_temp, _panda, _connect, self._sunnylink_status]
    start_y = int(rect.y) + METRIC_START_Y
@@ -4,8 +4,14 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
+import math
+
+import pyray as rl
+
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel


@@ -13,3 +19,16 @@ class MiciHomeLayoutSP(MiciHomeLayout):
  def __init__(self):
    super().__init__()
    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
+    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
+    self._chestnut_loading_icon.set_visible(False)
+    failed_idx = self._status_bar_layout.widgets.index(self._chestnut_failed_icon)
+    self._status_bar_layout.widgets.insert(failed_idx + 1, self._chestnut_loading_icon)
+
+  def _set_chestnut_visibility(self):
+    # stock has no loading tier: it shows green from the moment a big model is available. keep the
+    # pulse so the status bar and the onroad HUD agree on what loading looks like.
+    loading = ui_state.chestnut_state == ChestnutState.LOADING
+    self._chestnut_loading_icon._opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+    self._chestnut_loading_icon.set_visible(loading)
+    self._chestnut_icon.set_visible(not loading and ui_state.chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE))
+    self._chestnut_failed_icon.set_visible(ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
@@ -7,16 +7,37 @@ See the LICENSE.md file in the root directory for more details.
 import pyray as rl

 from openpilot.cereal import custom
-from openpilot.sunnypilot.models.default_model import get_default_model
+from openpilot.selfdrive.ui.mici.widgets.dialog import BigDialog
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_selected_bundle
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton
-from openpilot.selfdrive.ui.sunnypilot.layouts.settings.models import ModelsLayout
 from openpilot.selfdrive.ui.ui_state import ui_state, device
+from openpilot.selfdrive.ui.sunnypilot.model_info import (active_source, big_model_state, bundles_for_source, carrying_model,
+                                                           default_model_name, model_info, queued_name)
 from openpilot.system.ui.lib.application import FontWeight, gui_app
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import NavScroller

+def _model_info() -> tuple[str, str, str]:
+  """(active model, info header, info text) for the panel. Runner-matched: the
+  active line names what actually drives, and a notable big-model state takes
+  the info pair."""
+  source, active_name, other_name = model_info()
+  state = big_model_state()
+  _, _, carry_display = carrying_model()
+  if carry_display is None:
+    big = get_selected_bundle(ui_state.params, "chestnut")
+    carry_display = big.displayName if big else default_model_name("chestnut")
+  active_text = (carry_display or active_name).lower()
+  if state == 'failed':
+    return active_text, tr("big model"), tr("unavailable")
+  if state == 'loading':
+    return active_text, tr("big model"), tr("getting ready")
+  header = tr("small model") if source == "chestnut" else tr("big model")
+  return active_text, header, other_name.lower()
+
+
 class CurrentModelInfo(Widget):
  def __init__(self):
    super().__init__()
@@ -26,12 +47,12 @@ class CurrentModelInfo(Widget):
    header_color = rl.Color(255, 255, 255, int(255 * 0.9))
    subheader_color = rl.Color(255, 255, 255, int(255 * 0.9 * 0.65))
    max_width = int(self._rect.width - 20)
+    active_text, info_header, info_text = _model_info()
    self.current_model_header = UnifiedLabel(tr("active model"), 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
-    default_text = f"{get_default_model()} (Default)".lower()
-    self.current_model_text = UnifiedLabel(default_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)
+    self.current_model_text = UnifiedLabel(active_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)

-    self.info_header = UnifiedLabel("cache size", 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
-    self.info_text = UnifiedLabel("0 mb", 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN)
+    self.info_header = UnifiedLabel(info_header, 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
+    self.info_text = UnifiedLabel(info_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)

  def _render(self, _):
    self.current_model_header.set_position(self._rect.x + 20, self._rect.y - 10)
@@ -55,12 +76,13 @@ class ModelsLayoutMici(NavScroller):
    self._download_progress = "."
    self._download_frame = 0
    self._was_downloading = False
+    self._selection_source: str | None = None

    self.select_model_btn = BigButton(tr("select model"))
    self.select_model_btn.set_click_callback(self._show_folders)

    self.cancel_download_btn = BigButton(tr("cancel download"))
-    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadIndex"))
+    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadRef"))

    self.main_items = [self.current_model_info, self.select_model_btn, self.cancel_download_btn]
    self._scroller.add_widgets(self.main_items)
@@ -69,8 +91,7 @@ class ModelsLayoutMici(NavScroller):
  def model_manager(self):
    return ui_state.sm["modelManagerSP"]

-  def _get_grouped_bundles(self, favorites = None):
-    bundles = self.model_manager.availableBundles
+  def _get_grouped_bundles(self, bundles, favorites = None):
    folders = {}
    for bundle in bundles:
      folder = next((override.value for override in bundle.overrides if override.key == "folder"), "")
@@ -90,47 +111,70 @@ class ModelsLayoutMici(NavScroller):
  def _show_folders(self):
    self.focused_widget = self.select_model_btn

+    hardware_btns = []
+    active = active_source()
+    for source, label in (("qcom", tr("small models")), ("chestnut", tr("big models"))):
+      bundle = get_selected_bundle(ui_state.params, source)
+      value = (bundle.internalName if bundle else default_model_name(source)).lower()
+      if source == active:
+        value += f" ({tr('active')})"
+      btn = BigButton(label.lower(), value=value)
+      btn.set_click_callback(lambda s=source: self._select_hardware(s))
+      hardware_btns.append(btn)
+    self._push_selection_view(hardware_btns)
+
+  def _select_hardware(self, source):
+    self._selection_source = source
+
    favs = ui_state.params.get("ModelManager_Favs")
    favorites = set(favs.split(';')) if favs else set()

-    folders = self._get_grouped_bundles(favorites)
+    bundles = bundles_for_source(source)
+    if not bundles:
+      gui_app.push_widget(BigDialog(title=tr("No models available"),
+                                    description=tr("No models are available for this hardware yet. Connect to the internet and refresh the model list.")))
+      return
+    folders = self._get_grouped_bundles(bundles, favorites)
+
    folder_buttons = []
-    default_btn = BigButton(f"{get_default_model()} (Default)".lower())
-    default_btn.set_click_callback(self._select_default)
+    default_btn = BigButton(default_model_name(source).lower())
+    default_btn.set_click_callback(lambda s=source: self._select_default(s))
    folder_buttons.append(default_btn)

    for folder in sorted(folders.keys(), key=lambda f: max((bundle.index for bundle in folders[f]), default=-1), reverse=True):
-      if folder.lower() in ["release models", "master models", "favorites"]:
-        btn = BigButton(folder.lower())
-        btn.set_click_callback(lambda f=folder: self._select_folder(f))
-        if folder.lower() == "favorites":
-          folder_buttons.insert(0, btn)
-        else:
-          folder_buttons.append(btn)
+      btn = BigButton(folder.lower())
+      btn.set_click_callback(lambda f=folder: self._select_folder(f))
+      if folder.lower() == "favorites":
+        folder_buttons.insert(0, btn)
+      else:
+        folder_buttons.append(btn)
    self._push_selection_view(folder_buttons)

  def _pop_to_main(self):
    gui_app.pop_widgets_to(self)
+    self._scroller.scroll_panel.set_offset(0.0)

  def _select_model(self, bundle):
-    ui_state.params.put("ModelManager_DownloadIndex", bundle.index)
+    ui_state.params.put("ModelManager_DownloadRef", bundle.ref)
    self._pop_to_main()

-  def _select_default(self):
-    ui_state.params.remove("ModelManager_ActiveBundle")
+  def _select_default(self, source):
+    ui_state.params.remove(ACTIVE_BUNDLE_KEYS[source])
    self._pop_to_main()

  def _select_folder(self, folder_name):
+    source = self._selection_source
+    if source is None:  # folders are only reachable after picking a hardware
+      return
    favs = ui_state.params.get("ModelManager_Favs")
    favorites = set(favs.split(';')) if favs else set()

-    folders = self._get_grouped_bundles(favorites)
+    folders = self._get_grouped_bundles(bundles_for_source(source), favorites)
    bundles = sorted(folders.get(folder_name, []), key=lambda b: b.index, reverse=True)

    btns = []
    for bundle in bundles:
-      txt = bundle.displayName.lower()
-      btn = BigButton(txt)
+      btn = BigButton(bundle.displayName.lower())
      btn.set_click_callback(lambda b=bundle: self._select_model(b))
      btns.append(btn)
    self._push_selection_view(btns)
@@ -162,11 +206,10 @@ class ModelsLayoutMici(NavScroller):
    self._was_downloading = is_downloading

    self.current_model_info.current_model_header.set_text(tr("active model"))
-    default_model_text = f"{get_default_model()} (Default)".lower()
-    model_text = manager.activeBundle.displayName.lower() if manager.activeBundle.ref else default_model_text
-    self.current_model_info.current_model_text.set_text(model_text)
-    self.current_model_info.info_header.set_text(tr("cache size"))
-    self.current_model_info.info_text.set_text(f"{ModelsLayout.calculate_cache_size():.2f} MB")
+    active_text, info_header, info_text = _model_info()
+    self.current_model_info.current_model_text.set_text(active_text)
+    self.current_model_info.info_header.set_text(info_header)
+    self.current_model_info.info_text.set_text(info_text)

    if manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.failed:
      self.current_model_info.info_header.set_text(tr("error") + self._download_progress)
@@ -177,18 +220,29 @@ class ModelsLayoutMici(NavScroller):
      device.set_override_interactive_timeout(5)
      progress = 0.0
      count = 0
+      verifying = False
      for model in manager.selectedBundle.models:
        count += 1
        p = model.artifact.downloadProgress
-        if p.status == custom.ModelManagerSP.DownloadStatus.downloading:
+        if p.status in (custom.ModelManagerSP.DownloadStatus.downloading,
+                        custom.ModelManagerSP.DownloadStatus.verifying):
          progress += p.progress
+          verifying = verifying or p.status == custom.ModelManagerSP.DownloadStatus.verifying
        elif p.status in (custom.ModelManagerSP.DownloadStatus.downloaded,
                          custom.ModelManagerSP.DownloadStatus.cached):
          progress += 100.0

-      self.current_model_info.current_model_header.set_text(tr("downloading"))
+      self.current_model_info.current_model_header.set_text(tr("verifying") if verifying else tr("downloading"))
+      self.cancel_download_btn.set_text(tr("cancel verification") if verifying else tr("cancel download"))
      self.current_model_info.current_model_header._shimmer = True
-      self.current_model_info.current_model_text.set_text(f"{manager.selectedBundle.internalName.lower()}")
+      name_text = manager.selectedBundle.internalName.lower()
+      if queued := queued_name(manager.selectedBundle.ref):
+        name_text += f"  |  {queued.lower()} {tr('queued')}"
+      self.current_model_info.current_model_text.set_text(name_text)
      self.current_model_info.info_header.set_text(tr("progress") + self._download_progress)
      self.current_model_info.info_header._shimmer = True
      self.current_model_info.info_text.set_text(f"{progress/count:.2f}%")
+
+    elif manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloaded:
+      self.current_model_info.info_header.set_text(tr("downloaded"))
+      self.current_model_info.info_text.set_text(tr("downloaded"))
@@ -12,13 +12,23 @@ from openpilot.selfdrive.ui.mici.widgets.dialog import BigConfirmationDialog, Bi
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.sunnylink import SunnylinkLayoutMici
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.models import ModelsLayoutMici
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import gui_app
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr

 ICON_SIZE = 70
 BIG_ICON_SIZE = 110


+class SunnylinkBigButton(SettingsBigButton):
+  def __init__(self, *args, **kwargs):
+    super().__init__(*args, **kwargs)
+    self._label.set_font_weight(FontWeight.AUDIOWIDE)
+
+  def _get_label_font_size(self):
+    # Audiowide runs wider than Inter: "sunnylink" wraps to two lines at 64
+    return 56
+
+
 class SettingsLayoutSP(OP.SettingsLayout):
  def __init__(self):
    OP.SettingsLayout.__init__(self)
@@ -33,7 +43,7 @@ class SettingsLayoutSP(OP.SettingsLayout):
    self.icon_offroad_slider = gui_app.texture("icons_mici/settings/device/lkas.png", BIG_ICON_SIZE, BIG_ICON_SIZE)

    sunnylink_panel = SunnylinkLayoutMici()
-    sunnylink_btn = SettingsBigButton(tr("sunnylink"), "", gui_app.texture("icons_mici/settings/developer/ssh.png", 55, 55))
+    sunnylink_btn = SunnylinkBigButton(tr("sunnylink"), "", gui_app.texture("../../sunnypilot/selfdrive/assets/icons_mici/sunnylink.png", 76, 44))
    sunnylink_btn.set_click_callback(lambda: gui_app.push_widget(sunnylink_panel))

    models_panel = ModelsLayoutMici()
@@ -56,8 +66,8 @@ class SettingsLayoutSP(OP.SettingsLayout):

    items = self._scroller._items.copy()

-    items.insert(1, sunnylink_btn)
-    items.insert(2, models_btn)
+    items.insert(1, models_btn)
+    items.insert(5, sunnylink_btn)

    # front slots (only one ever visible at a time): exit-always-offroad, then enable-onroad
    items.insert(0, self._enable_offroad_btn_onroad)
@@ -0,0 +1,85 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.sunnypilot.models.fetcher import get_cached_bundles
+from openpilot.sunnypilot.models.helpers import get_active_source, get_selected_bundle, resolve_bundle_by_ref
+from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL, DEFAULT_MODEL
+
+
+def active_source() -> str:
+  return get_active_source(chestnut=ui_state.chestnut_present,
+                           chestnut_active=ui_state.chestnut_active, chestnut_loading=ui_state.chestnut_loading,
+                           offroad=ui_state.is_offroad())
+
+
+def bundles_for_source(source: str):
+  if source == active_source():
+    return ui_state.sm["modelManagerSP"].availableBundles
+  return get_cached_bundles(ui_state.params, source)
+
+
+def default_model(source: str) -> str:
+  return DEFAULT_BIG_MODEL if source == 'chestnut' else DEFAULT_MODEL
+
+
+def default_model_name(source: str) -> str:
+  return f"{default_model(source)} (Default)"
+
+
+def big_model_state() -> str | None:
+  """'failed' | 'loading' | None, from the same state the icons render."""
+  return {ChestnutState.UNCOMPILED: 'failed',
+          ChestnutState.FAILED: 'failed',
+          ChestnutState.LOADING: 'loading'}.get(ui_state.chestnut_state)
+
+
+def carrying_model() -> tuple[str | None, str | None, str | None]:
+  """(source, internal name, display name) of what actually drives. Runner-matched:
+  when a Default big cannot carry, stock modeld runs the Default small, never the
+  small slot's pick; a custom big has no automatic fallback yet -> (None, None, None)."""
+  source = active_source()
+  if source == "chestnut":
+    bundle = get_selected_bundle(ui_state.params, "chestnut")
+    if bundle:
+      return "chestnut", bundle.internalName, bundle.displayName
+    name = default_model_name("chestnut")
+    return "chestnut", name, name
+  if ui_state.chestnut_present:
+    if get_selected_bundle(ui_state.params, "chestnut") is None:
+      name = default_model_name("qcom")
+      return "qcom", name, name
+    return None, None, None
+  bundle = get_selected_bundle(ui_state.params, "qcom")
+  if bundle:
+    return "qcom", bundle.internalName, bundle.displayName
+  name = default_model_name("qcom")
+  return "qcom", name, name
+
+
+def queued_name(current_ref) -> str | None:
+  ref = ui_state.params.get("ModelManager_DownloadRef")
+  if ref and ref != current_ref:
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    if resolved := resolve_bundle_by_ref(ref, source_bundles):
+      return resolved[0].internalName
+  return None
+
+
+def model_info() -> tuple[str, str, str]:
+  """returns (active source, active model name, other model name)
+
+  Names come from the params slots, never modelManagerSP.activeBundle — the
+  manager republishes a tick after a chestnut change, so the stale bundle
+  would flash the wrong model."""
+  source = active_source()
+  other = "qcom" if source == "chestnut" else "chestnut"
+  active_bundle = get_selected_bundle(ui_state.params, source)
+  other_bundle = get_selected_bundle(ui_state.params, other)
+
+  active_name = active_bundle.displayName if active_bundle else default_model_name(source)
+  other_name = other_bundle.displayName if other_bundle else default_model_name(other)
+  return source, active_name, other_name
@@ -10,6 +10,7 @@ from openpilot.cereal import messaging, log, custom
 from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.selfdrive.ui.sunnypilot.layouts.settings.display import OnroadBrightness
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_active_source
 from openpilot.sunnypilot.sunnylink.sunnylink_state import SunnylinkState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.sunnypilot.widgets.screen_saver import ScreenSaverSP
@@ -43,6 +44,7 @@ class UIStateSP:
    self.screensaver_enabled: bool = False

    self.active_bundle = None
+    self.model_runner_tinygrad: bool = False
    self.blindspot: bool = False
    self.chevron_metrics = None
    self.custom_interactive_timeout: int = 0
@@ -150,7 +152,13 @@ class UIStateSP:
      self.has_icbm = self.CP_SP.intelligentCruiseButtonManagementAvailable and self.params.get_bool("IntelligentCruiseButtonManagement")

    self._enforce_constraints()
-    self.active_bundle = self.params.get("ModelManager_ActiveBundle")
+    source = get_active_source(chestnut=self.chestnut_present, chestnut_active=self.chestnut_active,
+                               chestnut_loading=self.chestnut_loading, offroad=self.is_offroad())
+    self.active_bundle = self.params.get(ACTIVE_BUNDLE_KEYS[source])
+    self.model_runner_tinygrad = self.active_bundle is not None and self.active_bundle.get("runner") == "tinygrad"
+    # stock only counts the default big model's compiled pkl. a downloaded big bundle runs on the
+    # chestnut just the same, so ChestnutState has to see it as available too.
+    self.chestnut_compiled = self.chestnut_compiled or self.model_runner_tinygrad
    self.blindspot = self.params.get_bool("BlindSpot")
    self.chevron_metrics = self.params.get("ChevronInfo")
    self.custom_interactive_timeout = self.params.get("InteractivityTimeout", return_default=True)
@@ -12,7 +12,7 @@ from openpilot.common.swaglog import cloudlog
 from openpilot.selfdrive.ui.lib.prime_state import PrimeState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.common.hardware import HARDWARE, PC
-from openpilot.selfdrive.modeld.helpers import usbgpu_compiled
+from openpilot.selfdrive.modeld.helpers import chestnut_compiled

 from openpilot.selfdrive.ui.sunnypilot.ui_state import UIStateSP, DeviceSP

@@ -28,6 +28,15 @@ class UIStatus(Enum):
  LONG_ONLY = "long_only"


+class ChestnutState(Enum):
+  DISCONNECTED = "disconnected"
+  UNCOMPILED = "uncompiled"
+  READY = "ready"
+  LOADING = "loading"
+  ACTIVE = "active"
+  FAILED = "failed"
+
+
 class UIState(UIStateSP):
  _instance: 'UIState | None' = None

@@ -82,10 +91,11 @@ class UIState(UIStateSP):
    self.always_on_dm: bool = self.params.get_bool("AlwaysOnDM")
    self.experimental_mode: bool = self.params.get_bool("ExperimentalMode")
    self.experimental_mode_confirmed: bool = self.params.get_bool("ExperimentalModeConfirmed")
-    self.usbgpu: bool = False
-    self.usbgpu_compiled: bool = usbgpu_compiled()
-    self.usbgpu_active: bool | None = self.params.get("UsbGpuActive")
-    self.usbgpu_loading: bool = self.params.get_bool("UsbGpuLoading")
+    self.chestnut_present: bool = False
+    self.chestnut_compiled: bool = chestnut_compiled()
+    self.chestnut_active: bool | None = None
+    self.chestnut_loading: bool = False
+    self.chestnut_state = ChestnutState.DISCONNECTED
    self.started: bool = False
    self.ignition: bool = False
    self.recording_audio: bool = False
@@ -131,6 +141,7 @@ class UIState(UIStateSP):
    self.sm.update(0)
    self._update_state()
    self._update_status()
+    self._update_chestnut_state()
    device.update()
    UIStateSP.update(self)

@@ -194,12 +205,35 @@ class UIState(UIStateSP):
        self.status = UIStatus.DISENGAGED
        self.started_frame = self.sm.frame
        self.started_time = time.monotonic()
+        self.chestnut_present = self.sm["deviceState"].chestnutPresent

      for callback in self._offroad_transition_callbacks:
        callback()

      self._started_prev = self.started

+  def _update_chestnut_state(self) -> None:
+    detected = self.sm["deviceState"].chestnutPresent
+    if not self.started:
+      self.chestnut_present = detected
+      self.chestnut_state = (ChestnutState.READY if detected and self.chestnut_compiled else
+                             ChestnutState.UNCOMPILED if detected else ChestnutState.DISCONNECTED)
+      return
+
+    model_seen = self.sm.recv_frame["modelV2"] > self.started_frame
+    if not self.chestnut_present:
+      self.chestnut_state = ChestnutState.DISCONNECTED
+    elif not self.chestnut_compiled:
+      self.chestnut_state = ChestnutState.UNCOMPILED
+    elif self.chestnut_state == ChestnutState.FAILED or not detected or (model_seen and (not self.sm.alive["modelV2"] or not self.sm["modelV2"].big)):
+      self.chestnut_state = ChestnutState.FAILED
+    elif self.chestnut_loading or not model_seen:
+      self.chestnut_state = ChestnutState.LOADING
+    elif self.chestnut_active is False:
+      self.chestnut_state = ChestnutState.FAILED
+    else:
+      self.chestnut_state = ChestnutState.ACTIVE
+
  def update_params(self) -> None:
    # For slower operations
    # Update longitudinal control state
@@ -216,12 +250,10 @@ class UIState(UIStateSP):
    self.always_on_dm = self.params.get_bool("AlwaysOnDM")
    self.experimental_mode = self.params.get_bool("ExperimentalMode")
    self.experimental_mode_confirmed = self.params.get_bool("ExperimentalModeConfirmed")
-    # keep usbgpu UI active until offroad transition when gpu disappears
-    self.usbgpu = self.sm["deviceState"].chestnutPresent or (self.usbgpu and self.started)
-    if not self.usbgpu_compiled:
-      self.usbgpu_compiled = usbgpu_compiled()
-    self.usbgpu_active = self.params.get("UsbGpuActive")
-    self.usbgpu_loading = self.params.get_bool("UsbGpuLoading")
+    if not self.chestnut_compiled:
+      self.chestnut_compiled = chestnut_compiled()
+    self.chestnut_active = self.params.get("ChestnutActive")
+    self.chestnut_loading = self.params.get_bool("ChestnutLoading")

    UIStateSP.update_params(self)

@@ -10,7 +10,6 @@ from openpilot.cereal import log, custom
 from opendbc.car import structs
 from opendbc.car.hyundai.values import HyundaiFlags
 from openpilot.common.params import Params
-from openpilot.selfdrive.selfdrived.events import ET
 from openpilot.sunnypilot.mads.helpers import MadsSteeringModeOnBrake, read_steering_mode_param, MADS_NO_ACC_MAIN_BUTTON
 from openpilot.sunnypilot.mads.state import StateMachine, GEARS_ALLOW_PAUSED_SILENT

@@ -34,7 +33,6 @@ class ModularAssistiveDrivingSystem:
    self.enabled = False
    self.active = False
    self.available = False
-    self.clear_no_entry = False
    self.lateral_mismatch_counter = 0
    self.allow_always = False
    self.no_main_cruise = False
@@ -220,8 +218,5 @@ class ModularAssistiveDrivingSystem:
    if not self.CP.passive and self.selfdrive.initialized:
      self.enabled, self.active = self.state_machine.update()

-    cat = self.selfdrive.state_machine.current_alert_types
-    self.clear_no_entry = (ET.ENABLE in cat or ET.USER_DISABLE in cat) and ET.NO_ENTRY not in cat
-
    # Copy of previous SelfdriveD states for MADS events handling
    self.selfdrive.enabled_prev = self.selfdrive.enabled
@@ -55,6 +55,19 @@ def cleanup_old_osm_data(files_to_remove: list[str]) -> None:
      shutil.rmtree(file, ignore_errors=False)


+def clear_downloaded_maps() -> None:
+  """Deletes downloaded OSM map data and resets params."""
+  path = f"{Paths.mapd_root()}/offline"
+  if os.path.exists(path):
+    shutil.rmtree(path, ignore_errors=True)
+
+  for param in ("OsmDownloadedDate", "OsmLocal", "OsmLocationName", "OsmLocationTitle",
+                "OsmStateName", "OsmStateTitle"):
+    params.remove(param)
+
+  cloudlog.info("mapd: downloaded maps cleared")
+
+
 def request_refresh_osm_location_data(nations: list[str], states: list[str] | None = None) -> None:
  params.put("OsmDownloadedDate", str(datetime.now().timestamp()), block=True)
  params.put_bool("OsmDbUpdatesCheck", False, block=True)
@@ -131,6 +144,10 @@ def main_thread():
    show_alert = bool(get_files_for_cleanup() and params.get_bool("OsmLocal"))
    set_offroad_alert("Offroad_OSMUpdateRequired", show_alert, "This alert will be cleared when new maps are downloaded.")

+    if params.get("Mapd_ClearCache"):
+      clear_downloaded_maps()
+      params.remove("Mapd_ClearCache")
+
    update_osm_db()
    live_map_sp.tick()
    rk.keep_time()
@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
 """

 import argparse
+import math
 import os
 import tempfile
 import time
@@ -66,14 +67,15 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
  if desire_key:
    shapes['desire'] = (input_shapes[desire_key][2],)

-  if is_supercombo and 'features_buffer' in input_shapes:
-    fb = input_shapes['features_buffer']
-    shapes['prev_feat'] = (fb[0], fb[2])
-
  for key, shape in input_shapes.items():
    if key not in (desire_key, 'features_buffer') and 'img' not in key:
      shapes[key] = tuple(shape)

+  if is_supercombo and 'features_buffer' in input_shapes:
+    fb = input_shapes['features_buffer']
+    feat_dim = math.prod(fb[2:])
+    shapes['prev_feat'] = (fb[0], feat_dim)
+
  sizes = [int(np.prod(size)) for size in shapes.values()]
  return shapes, sizes

@@ -117,8 +119,9 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
  }

  if features_buffer:
+    feat_dim = math.prod(features_buffer[2:])
    feat_q_len = frame_skip * features_buffer[1] if is_supercombo else frame_skip * (features_buffer[1] - 1) + 1
-    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], features_buffer[2]),
+    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], feat_dim),
                       dtype=np.float32), device=device).contiguous().realize()

  queues.update({key: Tensor(value, device='NPY').realize() for key, value in npy_arrays.items() if key in ('tfm', 'big_tfm')})
@@ -183,14 +186,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
    warped_dev = warped.to(Device.DEFAULT)
    Tensor.realize(packed_npy_inputs_dev, warped_dev)

-    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn).realize()
-    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn).realize()
+    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
+    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)

    unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
    unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))

    desire_dev = unpacked_dict['desire']
-    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn).realize()
+    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)

    inputs = {desire_key: desire_buf}
    for key, tensor_val in unpacked_dict.items():
@@ -199,7 +202,7 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,

    if 'prev_feat' in unpacked_dict:
      prev_feat_dev = unpacked_dict['prev_feat']
-      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).realize()
+      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).reshape(input_shapes['features_buffer'])

    if vision_runner:
      vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
@@ -211,7 +214,7 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,

    inputs.update({road_key: img, wide_key: big_img})
    if 'features_buffer' not in inputs:
-      inputs['features_buffer'] = sample_skip_fn(feat_q)
+      inputs['features_buffer'] = sample_skip_fn(feat_q).reshape(input_shapes['features_buffer'])

    policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
    if 'features_buffer' not in inputs and features_slice is not None:
@@ -295,7 +298,7 @@ def _load_policy_runners(args: argparse.Namespace) -> tuple[list, list]:


 if __name__ == "__main__":
-  if 'USB' in os.getenv('DEV', '') or os.getenv('USBGPU'):
+  if 'USB' in os.getenv('DEV', '') or os.getenv('CHESTNUT'):
    from openpilot.system.hardware.chestnut.flash import link_up
    for _ in range(10):
      if link_up():
@@ -9,7 +9,7 @@ See the LICENSE.md file in the root directory for more details.
 import os
 os.environ['GMMU'] = '0'
 from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.selfdrive.modeld.helpers import usbgpu_present, load_oob
+from openpilot.selfdrive.modeld.helpers import chestnut_present, load_oob
 import time
 import numpy as np
 import openpilot.cereal.messaging as messaging
@@ -84,14 +84,14 @@ class ModelState(ModelStateBase):
  inputs: dict[str, np.ndarray]
  prev_desire: np.ndarray

-  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool = False):
+  def __init__(self, cam_w: int, cam_h: int, chestnut: bool = False):
    ModelStateBase.__init__(self)

    env_pkl = os.environ.get('COMBINED_MODEL_PKL')
    if env_pkl and os.path.exists(env_pkl):
      model_bundle = None
    else:
-      model_bundle = get_active_bundle()
+      model_bundle = get_active_bundle(chestnut=chestnut)
    self.generation = model_bundle.generation if model_bundle is not None else None
    overrides = {override.key: override.value for override in model_bundle.overrides} if model_bundle else {}

@@ -99,7 +99,7 @@ class ModelState(ModelStateBase):
    self.LONG_SMOOTH_SECONDS = float(overrides.get('long', ".0"))
    self.MIN_LAT_CONTROL_SPEED = 0.3
    self.PLANPLUS_CONTROL: float = 1.0
-    self.usbgpu = usbgpu
+    self.chestnut = chestnut

    pkl_path = _find_driving_pkl(model_bundle)
    assert pkl_path is not None, "No driving pkl found — all models must be compiled with compile_modeld.py"
@@ -110,7 +110,7 @@ class ModelState(ModelStateBase):
    jits = load_oob(open_file_chunked(pkl_path))

    self.WARP_DEV = 'QCOM' if COMMA_HARDWARE else 'CPU'
-    self.DEV = 'AMD' if self.usbgpu else self.WARP_DEV
+    self.DEV = 'AMD' if self.chestnut else self.WARP_DEV
    self.QUEUE_DEV = self.DEV
    metadata = jits['metadata']

@@ -185,7 +185,7 @@ class ModelState(ModelStateBase):
    else:
      self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=frame_tensor, big_frame=big_frame_tensor)

-    if self.usbgpu:
+    if self.chestnut:
      self.warmup()

  def warmup(self) -> None:
@@ -287,7 +287,7 @@ class ModelState(ModelStateBase):
      buf[0, :-1] = buf[0, 1:]
      buf[0, -1, :] = outputs['desired_curvature'][0, :] if not self.mlsim else 0

-    if self.usbgpu and not np.all(np.isfinite(outputs.get('plan', np.array([0.])))):
+    if self.chestnut and not np.all(np.isfinite(outputs.get('plan', np.array([0.])))):
      cloudlog.error("model output not finite, dropping frame")
      return None

@@ -327,13 +327,13 @@ def main(demo=False):
  setproctitle(PROCESS_NAME)
  config_realtime_process(7, 54)

-  USBGPU = usbgpu_present()
-  if USBGPU:
+  CHESTNUT = chestnut_present()
+  if CHESTNUT:
    os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'

  params = Params()
-  params.put_bool("UsbGpuLoading", USBGPU)
-  params.remove("UsbGpuActive")
+  params.put_bool("ChestnutLoading", CHESTNUT)
+  params.remove("ChestnutActive")

  # visionipc clients
  while True:
@@ -362,31 +362,31 @@ def main(demo=False):
  st = time.monotonic()

  model = None
-  if USBGPU:
+  if CHESTNUT:
    import threading
    def load():
      nonlocal model
-      model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, usbgpu=True)
+      model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, chestnut=True)
    t = threading.Thread(target=load, daemon=True)
    t.start()
    t.join(60)
    if model is None:
-      params.put_bool("UsbGpuActive", False)
-      raise RuntimeError("eGPU model load failed or timed out (60s)")
-    params.put_bool("UsbGpuActive", True)
+      params.put_bool("ChestnutActive", False)
+      raise RuntimeError("chestnut model load failed or timed out (60s)")
+    params.put_bool("ChestnutActive", True)
  else:
-    model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, usbgpu=False)
+    model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, chestnut=False)

-  params.put_bool("UsbGpuLoading", False)
+  params.put_bool("ChestnutLoading", False)
  cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")

  # messaging
-  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if USBGPU else [])
+  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if CHESTNUT else [])
  pm = PubMaster(pub_socks)
  sm = SubMaster(["deviceState", "carState", "narrowRoadCameraState", "extrinsicsCalibration", "driverMonitoringState", "carControl", "lateralDelay"])

  publish_state = PublishState()
-  chestnut_state = ChestnutState(pm, USBGPU) if USBGPU else None
+  chestnut_state = ChestnutState(pm, CHESTNUT) if CHESTNUT else None

  # setup filter to track dropped frames
  frame_dropped_filter = FirstOrderFilter(0., 10., 1. / model.constants.MODEL_FREQ)
@@ -524,7 +524,7 @@ def main(demo=False):
      fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                     publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                     frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen, meta_constants)
-      modelv2_send.modelV2.big = model.usbgpu
+      modelv2_send.modelV2.big = model.chestnut

      desire_state = modelv2_send.modelV2.meta.desireState
      l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
@@ -190,8 +190,8 @@ def tmp_path():

 def patch_modeld(monkeypatch):
  def _patch(bundle):
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)

  return _patch

@@ -59,8 +59,8 @@ class TestFindDrivingPkl(OpenpilotTestCase):
 class TestModelStateCombinedInit(OpenpilotTestCase):
  def test_asserts_when_no_pkl(self, monkeypatch):
    bundle = DummyBundle(models=[], is_20hz=True)
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
    with self.assertRaisesRegex(AssertionError, "No driving pkl found"):
      ModelState(cam_w=CAM_W, cam_h=CAM_H)

@@ -195,3 +195,85 @@ class TestReadFileChunkedToDisk(OpenpilotTestCase):

      assert out.parent == Path(d)
      assert out.read_bytes() == payload
+
+
+class Test4DFeaturesBuffer(OpenpilotTestCase):
+  def test_get_policy_npy_shapes_4d(self):
+    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
+    input_shapes = {
+      'desire_pulse': (1, 25, 8),
+      'features_buffer': (1, 24, 32, 512),  # compare 4d to 3d for regression
+      'traffic_convention': (1, 2),
+      'action_t': (1, 2)
+    }
+    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
+    assert shapes['prev_feat'] == (1, 16384)
+    assert sizes == [8, 2, 2, 16384]
+
+  def test_get_policy_npy_shapes_3d(self):
+    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
+    input_shapes = {
+      'desire_pulse': (1, 25, 8),
+      'features_buffer': (1, 24, 512),
+      'traffic_convention': (1, 2),
+      'action_t': (1, 2)
+    }
+    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
+    assert shapes['prev_feat'] == (1, 512)
+    assert sizes == [8, 2, 2, 512]
+
+
+class TestStockCompileModeldEquivalence(OpenpilotTestCase):
+  def test_get_policy_npy_shapes_matches_stock(self):
+    from openpilot.selfdrive.modeld.compile_modeld import get_policy_npy_shapes as stock_get_policy_npy_shapes
+    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes as sunny_get_policy_npy_shapes
+
+    stock_input_shapes = {
+      'desire_pulse': (1, 25, 8),
+      'features_buffer': (1, 24, 512), # see below comment
+      'traffic_convention': (1, 2),
+      'action_t': (1, 2),
+    }
+
+    stock_shapes, stock_sizes = stock_get_policy_npy_shapes(stock_input_shapes)
+    sunny_shapes, sunny_sizes = sunny_get_policy_npy_shapes(stock_input_shapes, is_supercombo=True)
+
+    assert sunny_shapes == stock_shapes
+    assert sunny_sizes == stock_sizes
+    assert sunny_shapes['prev_feat'] == (1, 512)
+
+  def test_make_input_queues_full_stock_equivalence(self):
+    from openpilot.selfdrive.modeld.compile_modeld import make_input_queues as stock_make_input_queues
+    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_supercombo_input_queues as sunny_make_supercombo_input_queues
+    input_shapes = {
+      'img': (1, 12, 128, 256),
+      'desire_pulse': (1, 25, 8),
+      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
+      'traffic_convention': (1, 2),
+      'action_t': (1, 2),
+    }
+    frame_skip = 4
+
+    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
+    sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
+    assert set(sunny_queues.keys()) == set(stock_queues.keys())
+    for key in stock_queues:
+      assert sunny_queues[key].shape == stock_queues[key].shape, \
+        f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
+    assert set(sunny_npy.keys()) == set(stock_npy.keys())
+    for key in stock_npy:
+      assert sunny_npy[key].shape == stock_npy[key].shape, \
+        f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"
+
+  def test_make_warp_queues_stock_equivalence(self):
+    from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
+    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues
+    stock_vision_shapes = {'img': (1, 12, 128, 256)}  # for now?
+    stock_queues, stock_npy = stock_make_warp_queues(stock_vision_shapes, frame_skip=4, device='NPY')
+    sunny_queues, sunny_npy = sunny_make_warp_queues(device='NPY')
+
+    assert set(sunny_npy.keys()) == set(stock_npy.keys()) == {'tfm', 'big_tfm'}
+    for key in sunny_npy:
+      assert sunny_npy[key].shape == stock_npy[key].shape == (3, 3)
+
+
@@ -9,8 +9,8 @@ from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL, DEFAULT_BIG_MO


 def get_default_model() -> str:
-  show_big_model = (ui_state.usbgpu
-                    and (ui_state.usbgpu_active or ui_state.usbgpu_loading or ui_state.is_offroad()))
+  show_big_model = (ui_state.chestnut_present
+                    and (ui_state.chestnut_active or ui_state.chestnut_loading or ui_state.is_offroad()))

  return DEFAULT_BIG_MODEL if show_big_model else DEFAULT_MODEL

@@ -13,8 +13,6 @@ from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.hardware.hw import Paths
 from openpilot.sunnypilot.models.helpers import is_bundle_version_compatible
-from openpilot.selfdrive.modeld.helpers import usbgpu_present
-
 from openpilot.cereal import custom


@@ -140,45 +138,53 @@ class ModelCache:

 class ModelFetcher:
  """Handles fetching and caching of model data from remote source"""
-  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v20.json"
-  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v21.json"
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v21.json"
+  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v22.json"
+
+  MODEL_SOURCES = {
+    "qcom": (MODEL_URL, ""),
+    "chestnut": (MODEL_URL_CHESTNUT, "_Chestnut"),
+  }

  def __init__(self, params: Params):
    self.params = params
    self.model_parser = ModelParser()
-    self._is_usbgpu: bool | None = None
-    self.model_cache = ModelCache(params)
-    self.model_url = self.MODEL_URL
-    self._update_model_source()
+    self.model_caches = {
+      source: ModelCache(params, suffix=suffix)
+      for source, (_, suffix) in self.MODEL_SOURCES.items()
+    }
+    self._refetched: set[str] = set()
+    self.params.put("ModelManager_ActiveJson", {
+      "qcom": self.MODEL_URL,
+      "chestnut": self.MODEL_URL_CHESTNUT,
+    }, block=True)

-  def _update_model_source(self) -> None:
-    """Updates what json to use based on usbgpu availability"""
-    is_usbgpu = usbgpu_present()
-    if is_usbgpu != self._is_usbgpu:
-      self._is_usbgpu = is_usbgpu
-      self.model_cache = ModelCache(self.params, suffix="_USBGPU" if is_usbgpu else "")
-      self.model_url = self.MODEL_URL_USBGPU if is_usbgpu else self.MODEL_URL
-      self.params.put("ModelManager_ActiveJson", self.model_url, block=True)
+  @staticmethod
+  def active_source(chestnut_present: bool) -> str:
+    return "chestnut" if chestnut_present else "qcom"

-  def _fetch_and_cache_models(self) -> list[custom.ModelManagerSP.ModelBundle] | None:
+  def _fetch_and_cache_models(self, source: str) -> list[custom.ModelManagerSP.ModelBundle] | None:
    """Fetches fresh model data from remote and updates cache.
    Returns None on transport errors. Raises on 404 and other fatal HTTP errors.
    """
+    model_url, _ = self.MODEL_SOURCES[source]
    try:
-      response = requests.get(self.model_url, timeout=10)
+      response = requests.get(model_url, timeout=10)

      # Explicitly handle 404 differently
      if response.status_code == 404:
-        cloudlog.error(f"Models URL returned 404 Not Found: {self.model_url}")
-        raise HTTPError(f"404 Not Found: {self.model_url}", response=response)
+        cloudlog.error(f"Models URL returned 404 Not Found: {model_url}")
+        raise HTTPError(f"404 Not Found: {model_url}", response=response)

      # Raise for any other 4xx/5xx
      response.raise_for_status()

      json_data = response.json()
-      self.model_cache.set(json_data)
-      cloudlog.debug("Successfully updated models cache")
-      return self.model_parser.parse_models(json_data)
+      parsed = self.model_parser.parse_models(json_data)
+      if parsed:
+        self.model_caches[source].set(json_data)
+        cloudlog.debug(f"Successfully updated models cache for {source}")
+      return parsed

    except ConnectionError as e:
      cloudlog.warning(f"DNS/connection error while fetching models: {e}")
@@ -191,16 +197,40 @@ class ModelFetcher:

    return None

-  def get_available_bundles(self) -> list[custom.ModelManagerSP.ModelBundle]:
-    """Gets the list of available models, with smart cache handling"""
-    self._update_model_source()
-    cached_data, is_expired = self.model_cache.get()
+  @staticmethod
+  def _cache_matches_source(source: str, cached_data: dict) -> bool:
+    bundles = cached_data.get("bundles", [])
+    if source == "chestnut":
+      return any(bundle.get("is_big") is True for bundle in bundles)
+    return not any(bundle.get("is_big") is True for bundle in bundles)
+
+  def get_bundles_for_source(self, source: str) -> list[custom.ModelManagerSP.ModelBundle]:
+    if source not in self.MODEL_SOURCES:
+      cloudlog.warning(f"Unknown model source: {source}")
+      return []
+
+    cached_data, is_expired = self.model_caches[source].get()

    if cached_data and not is_expired:
-      cloudlog.debug("Using valid cached models data")
-      return self.model_parser.parse_models(cached_data)
+      # a source is refetched over a mismatch at most once per process: if the fresh
+      # manifest still mismatches, the URL is authoritative and the cache is trusted
+      if self._cache_matches_source(source, cached_data) or source in self._refetched:
+        try:
+          parsed = self.model_parser.parse_models(cached_data)
+        except Exception:
+          cloudlog.warning(f"Failed to parse cached models for {source}; refetching", exc_info=True)
+        else:
+          if parsed:
+            cloudlog.debug(f"Using valid cached models data for source {source}")
+            return parsed
+          # a source-matching cache that yields no valid bundles is stale (e.g. an old
+          # manifest version) - do not trust it, refetch so the source is repopulated
+          cloudlog.warning(f"Cached models for {source} have no valid bundles; refetching")
+      else:
+        self._refetched.add(source)
+        cloudlog.warning(f"Cached models for {source} not valid; refetching once")

-    fetched_bundles = self._fetch_and_cache_models()
+    fetched_bundles = self._fetch_and_cache_models(source)
    if fetched_bundles is not None:
      return fetched_bundles

@@ -208,12 +238,33 @@ class ModelFetcher:
      cloudlog.warning("Failed to fetch fresh data and no cache available")

    cloudlog.warning("Failed to fetch fresh data. Using expired cache as fallback")
-    return self.model_parser.parse_models(cached_data)
+    try:
+      return self.model_parser.parse_models(cached_data)
+    except Exception:
+      return []
+
+
+def get_cached_bundles(params: Params, source: str) -> list[custom.ModelManagerSP.ModelBundle]:
+
+  if source not in ModelFetcher.MODEL_SOURCES:
+    cloudlog.warning(f"Unknown model source: {source}")
+    return []
+  _, suffix = ModelFetcher.MODEL_SOURCES[source]
+  cached_data = params.get(f"ModelManager_ModelsCache{suffix}")
+  if not cached_data:
+    return []
+  try:
+    return ModelParser.parse_models(cached_data)
+  except Exception as e:
+    cloudlog.warning(f"Failed to parse cached models for source {source}: {e}")
+    return []
+

 if __name__ == "__main__":
+  from openpilot.selfdrive.modeld.helpers import chestnut_present
  params = Params()
  model_fetcher = ModelFetcher(params)
-  bundles = model_fetcher.get_available_bundles()
+  bundles = model_fetcher.get_bundles_for_source(ModelFetcher.active_source(chestnut_present()))
  for bundle in bundles:
    for model in bundle.models:
      model_overrides = {override.key: override.value for override in bundle.overrides}
@@ -16,14 +16,20 @@ from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
 from openpilot.sunnypilot.models.constants import Meta, MetaSimPose, MetaTombRaider
 from openpilot.common.hardware.hw import Paths
+from openpilot.selfdrive.modeld.helpers import chestnut_present

 # SET ME TO THE EXACT JSON VERSION WE SET IN SUNNYPILOT_MODELS REPO
-REQUIRED_JSON_VERSION = 17
+REQUIRED_JSON_VERSION = 18

 CUSTOM_MODEL_PATH = Paths.model_root()
 METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'
 ModelManager = custom.ModelManagerSP
-_LAST_VALIDATED_RAW = None
+
+ACTIVE_BUNDLE_KEYS = {
+  "qcom": "ModelManager_ActiveBundle",
+  "chestnut": "ModelManager_ActiveBundleChestnut",
+}
+_LAST_VALIDATED_RAW: dict[str, dict | None] = {}


 def _compute_hash(file_path: str) -> str | None:
@@ -86,11 +92,11 @@ def _bundle_needs_reset(active_bundle: custom.ModelManagerSP.ModelBundle, availa
  if available_bundles is not None:
    matching_bundle = None
    for bundle in available_bundles:
-      if getattr(active_bundle, 'ref', None) and getattr(bundle, 'ref', None):
+      if active_bundle.ref and bundle.ref:
        if active_bundle.ref == bundle.ref:
          matching_bundle = bundle
          break
-      elif getattr(active_bundle, 'internalName', None) == getattr(bundle, 'internalName', None):
+      elif active_bundle.internalName == bundle.internalName:
        matching_bundle = bundle
        break

@@ -98,49 +104,81 @@ def _bundle_needs_reset(active_bundle: custom.ModelManagerSP.ModelBundle, availa
      return True
    if active_bundle.minimumSelectorVersion != matching_bundle.minimumSelectorVersion:
      return True
-
-    active_runner = getattr(active_bundle, 'runner', None)
-    matching_runner = getattr(matching_bundle, 'runner', None)
-    if active_runner is not None and matching_runner is not None:
-      if getattr(active_runner, 'raw', active_runner) != getattr(matching_runner, 'raw', matching_runner):
-        return True
+    if active_bundle.runner != matching_bundle.runner:
+      return True
    if set(_bundle_artifacts(active_bundle)) != set(_bundle_artifacts(matching_bundle)):
      return True

  return not _bundle_is_valid_locally(active_bundle)


-def validate_active_bundle(params: Params, available_bundles: list[custom.ModelManagerSP.ModelBundle] | None = None) -> None:
-  global _LAST_VALIDATED_RAW
-
-  raw_bundle = params.get("ModelManager_ActiveBundle")
-  if not raw_bundle:
-    return
-
-  if raw_bundle == _LAST_VALIDATED_RAW:
-    return
-
-  active_bundle = get_active_bundle(params, raw_bundle_dict=raw_bundle)
-  if active_bundle is None or _bundle_needs_reset(active_bundle, available_bundles):
-    cloudlog.warning("Active model bundle invalid; resetting to default")
-    params.remove("ModelManager_ActiveBundle")
-    params.put("ModelRunnerTypeCache", int(custom.ModelManagerSP.Runner.stock), block=True)
-    _LAST_VALIDATED_RAW = None
-  else:
-    _LAST_VALIDATED_RAW = raw_bundle
-
-
-def get_active_bundle(params: Params | None = None, raw_bundle_dict: dict | bytes | None = None) -> "custom.ModelManagerSP.ModelBundle | None":
-  params = params or Params()
+def _parse_active_bundle(raw_bundle) -> "custom.ModelManagerSP.ModelBundle | None":
  try:
-    active_bundle_dict = raw_bundle_dict if raw_bundle_dict is not None else (params.get("ModelManager_ActiveBundle") or {})
-    if isinstance(active_bundle_dict, dict) and active_bundle_dict and is_bundle_version_compatible(active_bundle_dict):
-      return custom.ModelManagerSP.ModelBundle(**active_bundle_dict)
+    if isinstance(raw_bundle, dict) and raw_bundle and is_bundle_version_compatible(raw_bundle):
+      return custom.ModelManagerSP.ModelBundle(**raw_bundle)
  except Exception:
    pass
  return None


+def get_selected_bundle(params: Params | None = None, source: str = "qcom") -> "custom.ModelManagerSP.ModelBundle | None":
+  params = params or Params()
+  return _parse_active_bundle(params.get(ACTIVE_BUNDLE_KEYS[source]))
+
+
+def get_active_source(chestnut: bool | None = None, chestnut_active: bool | None = None,
+                      chestnut_loading: bool | None = None, offroad: bool | None = None) -> str:
+  if chestnut is None:
+    chestnut = chestnut_present()
+  state_valid = chestnut_active is not None or chestnut_loading is not None or offroad is not None
+  big_active = chestnut and (not state_valid or chestnut_active or chestnut_loading or offroad)
+  return "chestnut" if big_active else "qcom"
+
+
+def get_active_bundle(params: Params | None = None, *, chestnut: bool | None = None) -> "custom.ModelManagerSP.ModelBundle | None":
+  # no cross-slot fallback: an empty active slot means the hardware default, which
+  # only stock modeld can run - modeld_v2 requires a real bundle
+  params = params or Params()
+  return get_selected_bundle(params, get_active_source(chestnut=chestnut))
+
+
+def resolve_bundle_by_ref(
+  ref: str, source_bundles: dict[str, list[custom.ModelManagerSP.ModelBundle]],
+) -> "tuple[custom.ModelManagerSP.ModelBundle, str] | None":
+  for source, bundles in source_bundles.items():
+    for bundle in bundles:
+      if bundle.ref == ref:
+        return bundle, source
+  return None
+
+
+def _validate_active_bundle(params: Params, source: str, available_bundles: list[custom.ModelManagerSP.ModelBundle] | None = None) -> None:
+  global _LAST_VALIDATED_RAW
+
+  key = ACTIVE_BUNDLE_KEYS[source]
+  raw_bundle = params.get(key)
+  if not raw_bundle:
+    return
+
+  if _LAST_VALIDATED_RAW.get(key) == raw_bundle:
+    return
+
+  active_bundle = _parse_active_bundle(raw_bundle)
+  if active_bundle is None or _bundle_needs_reset(active_bundle, available_bundles):
+    cloudlog.warning(f"Active model bundle invalid for {source}; resetting to default")
+    params.remove(key)
+    _LAST_VALIDATED_RAW[key] = None
+  else:
+    _LAST_VALIDATED_RAW[key] = raw_bundle
+
+
+def validate_active_bundles(params: Params, source_bundles: dict[str, list[custom.ModelManagerSP.ModelBundle]]) -> None:
+  # an empty list means the fetch failed, not that the catalog dropped the bundle
+  for source, bundles in source_bundles.items():
+    _validate_active_bundle(params, source, bundles or None)
+  get_active_model_runner(params, force_check=True)
+
+
 def get_active_model_runner(params: Params | None = None, force_check: bool = False) -> int:
  params = params or Params()
  cached_runner_type = params.get("ModelRunnerTypeCache")
@@ -17,12 +17,17 @@ from openpilot.common.hardware.hw import Paths

 from openpilot.cereal import messaging, custom
 from openpilot.sunnypilot.models.fetcher import ModelFetcher
-from openpilot.sunnypilot.models.helpers import get_active_bundle, validate_active_bundle, verify_file
+from openpilot.sunnypilot.models.helpers import (ACTIVE_BUNDLE_KEYS, get_active_bundle, get_selected_bundle,
+                                                  resolve_bundle_by_ref, validate_active_bundles, verify_file)

 # (connect, read) seconds. read is per-request inactivity, not a total cap
 DOWNLOAD_TIMEOUT = (30, 30)


+class DownloadCancelled(Exception):
+  pass
+
+
 class ModelManagerSP:
  """Manages model downloads and status reporting"""

@@ -30,11 +35,25 @@ class ModelManagerSP:
    self.params = Params()
    self.model_fetcher = ModelFetcher(self.params)
    self.pm = messaging.PubMaster(["modelManagerSP"])
+    self.sm = messaging.SubMaster(["deviceState"])
+    self.chestnut_present = False
    self.available_models: list[custom.ModelManagerSP.ModelBundle] = []
+    self.source_models: dict[str, list[custom.ModelManagerSP.ModelBundle]] = {}
    self.selected_bundle: custom.ModelManagerSP.ModelBundle = None
-    self.active_bundle: custom.ModelManagerSP.ModelBundle = get_active_bundle(self.params)
+    self.active_bundle: custom.ModelManagerSP.ModelBundle = get_active_bundle(self.params, chestnut=self.chestnut_present)
    self._chunk_size = 128 * 1000  # 128 KB chunks
    self._download_start_times: dict[str, float] = {}  # Track start time per model
+    self._download_ref: bytes | str | None = None
+
+  def _download_interrupted(self) -> bool:
+    # only removal cancels: a different ref is a queued selection that
+    # _release_download_ref leaves in place for the next tick
+    return self.params.get("ModelManager_DownloadRef") is None
+
+  def _release_download_ref(self) -> None:
+    if self.params.get("ModelManager_DownloadRef") == self._download_ref:
+      self.params.remove("ModelManager_DownloadRef")
+    self._download_ref = None

  def _sync_artifact_progress(self, source_artifact) -> None:
    """Mirror download progress to all artifacts sharing the same filename in the selected bundle."""
@@ -76,8 +95,8 @@ class ModelManagerSP:
          f.write(chunk)
          bytes_downloaded += len(chunk)

-          if self.params.get("ModelManager_DownloadIndex") is None:
-            raise Exception("Download cancelled")
+          if self._download_interrupted():
+            raise DownloadCancelled("Download cancelled")

          if total_size > 0:
            progress = (bytes_downloaded / total_size) * 100
@@ -90,7 +109,7 @@ class ModelManagerSP:
    # Clean up start time after download completes
    del self._download_start_times[model.fileName]

-  async def _download_chunked(self, base_url: str, base_path: str, artifact) -> None:
+  async def _download_chunked(self, base_url: str, base_path: str, artifact, skip: frozenset[int] | set[int] = frozenset()) -> None:
    from openpilot.common.file_chunker import get_chunk_name, get_manifest_path

    num_chunks = len(artifact.chunks)
@@ -102,8 +121,11 @@ class ModelManagerSP:

    # Shared connection saves a TCP+TLS handshake per chunk.
    # Keep sequential: the link saturates on one stream and Session is not thread-safe.
+    completed = len(skip)
    with requests.Session() as session:
      for i, _ in enumerate(artifact.chunks):
+        if i in skip:
+          continue
        chunk_url = get_chunk_name(base_url, i, num_chunks)
        chunk_path = get_chunk_name(base_path, i, num_chunks)
        chunk_downloaded = 0
@@ -114,15 +136,16 @@ class ModelManagerSP:
            for data in response.iter_content(chunk_size=self._chunk_size):
              f.write(data)
              chunk_downloaded += len(data)
-              if self.params.get("ModelManager_DownloadIndex") is None:
-                raise Exception("Download cancelled")
+              if self._download_interrupted():
+                raise DownloadCancelled("Download cancelled")
              intra = chunk_downloaded / max(chunk_size, 1)
-              progress = min(99.0, ((i + intra) / num_chunks) * 100)
+              progress = min(99.0, ((completed + intra) / num_chunks) * 100)
              artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloading
              artifact.downloadProgress.progress = progress
              artifact.downloadProgress.eta = self._calculate_eta(artifact.fileName, progress)
              self._sync_artifact_progress(artifact)
              self._report_status()
+        completed += 1

    with open(manifest_path, 'w') as f:  # noqa: ASYNC230
      f.write(str(num_chunks))
@@ -133,6 +156,8 @@ class ModelManagerSP:
  async def _process_artifact(self, artifact, destination_path: str) -> None:
    if not artifact.downloadUri.uri:
      return None
+    if self._download_interrupted():
+      raise DownloadCancelled("Download cancelled")

    url = artifact.downloadUri.uri
    expected_hash = artifact.downloadUri.sha256
@@ -140,21 +165,23 @@ class ModelManagerSP:
    full_path = os.path.join(destination_path, filename)

    try:
+      # progress counts only valid chunks so a resumed download continues the
+      # bar from where verification left it, instead of falling back to zero
      is_cached = False
+      valid_chunks: set[int] = set()
      if len(artifact.chunks) > 0:
        from openpilot.common.file_chunker import get_chunk_name
        num_chunks = len(artifact.chunks)
-        chunks_valid = True
        for i, chunk in enumerate(artifact.chunks):
-          chunk_path = get_chunk_name(full_path, i, num_chunks)
-          if not await verify_file(chunk_path, chunk.sha256):
-            chunks_valid = False
-            break
-          artifact.downloadProgress.progress = ((i + 1) / num_chunks) * 100
+          if self._download_interrupted():
+            raise DownloadCancelled("Download cancelled")
+          if await verify_file(get_chunk_name(full_path, i, num_chunks), chunk.sha256):
+            valid_chunks.add(i)
+          artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.verifying
+          artifact.downloadProgress.progress = (len(valid_chunks) / num_chunks) * 100
          self._sync_artifact_progress(artifact)
          self._report_status()
-        if chunks_valid and num_chunks > 0:
-          is_cached = True
+        is_cached = len(valid_chunks) == num_chunks
      else:
        if await verify_file(full_path, expected_hash):
          is_cached = True
@@ -168,7 +195,7 @@ class ModelManagerSP:
        return

      if len(artifact.chunks) > 0:
-        await self._download_chunked(url, full_path, artifact)
+        await self._download_chunked(url, full_path, artifact, skip=valid_chunks)
        from openpilot.common.file_chunker import get_chunk_name
        for i, chunk in enumerate(artifact.chunks):
          chunk_path = get_chunk_name(full_path, i, len(artifact.chunks))
@@ -185,6 +212,17 @@ class ModelManagerSP:
      self._sync_artifact_progress(artifact)
      self._report_status()

+    except DownloadCancelled:
+      # a cancel keeps whatever is on disk: complete chunks resume the next attempt
+      self._download_start_times.pop(artifact.fileName, None)
+      artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.failed
+      artifact.downloadProgress.eta = 0
+      self._sync_artifact_progress(artifact)
+      if self.selected_bundle:
+        self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.failed
+      self._report_status()
+      raise
+
    except Exception as e:
      cloudlog.error(f"Error downloading {filename}: {str(e)}")
      for f in [full_path] + [p for p in (os.path.join(destination_path, f) for f in os.listdir(destination_path)) if filename in p]:
@@ -216,8 +254,7 @@ class ModelManagerSP:
    model_manager_state.availableBundles = self.available_models
    self.pm.send('modelManagerSP', msg)

-  async def _download_bundle(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str) -> None:
-    """Downloads all models in a bundle"""
+  async def _download_bundle(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str, source: str) -> None:
    self.selected_bundle = model_bundle
    self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.downloading
    for model in self.selected_bundle.models:
@@ -239,10 +276,11 @@ class ModelManagerSP:
          seen_artifacts.add(artifact.fileName)
          await self._process_artifact(artifact, destination_path)

-      self.active_bundle = self.selected_bundle
-      self.active_bundle.status = custom.ModelManagerSP.DownloadStatus.downloaded
-      self.params.put("ModelManager_ActiveBundle", self.active_bundle.to_dict(), block=True)
-      self.selected_bundle = None
+      if self._download_interrupted():
+        raise DownloadCancelled("Download cancelled")
+      self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.downloaded
+      self.params.put(ACTIVE_BUNDLE_KEYS[source], model_bundle.to_dict(), block=True)
+      self.active_bundle = get_active_bundle(self.params, chestnut=self.chestnut_present)

    except Exception:
      if self.selected_bundle is not None:
@@ -252,9 +290,30 @@ class ModelManagerSP:
    finally:
      self._report_status()

-  def download(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str) -> None:
+  def download(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str, source: str) -> None:
    """Main entry point for downloading a model bundle"""
-    asyncio.run(self._download_bundle(model_bundle, destination_path))
+    asyncio.run(self._download_bundle(model_bundle, destination_path, source))
+
+  def _process_download_requests(self) -> None:
+    # loops so a ref queued during a download starts in the same tick, without
+    # the bar dropping to idle for a tick between the two transfers
+    last_ref = None
+    while (ref_to_download := self.params.get("ModelManager_DownloadRef")) is not None:
+      if ref_to_download == last_ref:  # a repeating ref falls back to the next tick instead of spinning
+        return
+      last_ref = ref_to_download
+      resolved = resolve_bundle_by_ref(ref_to_download, self.source_models)
+      if not resolved:
+        return
+      model_to_download, source = resolved
+      self._download_ref = ref_to_download
+      try:
+        self.download(model_to_download, Paths.model_root(), source)
+      except Exception as e:
+        cloudlog.exception(e)
+      finally:
+        self._release_download_ref()
+        self.selected_bundle = None

  def main_thread(self) -> None:
    """Main thread for model management"""
@@ -262,21 +321,14 @@ class ModelManagerSP:

    while True:
      try:
-        self.available_models = self.model_fetcher.get_available_bundles()
-        validate_active_bundle(self.params, self.available_models)
-        self.active_bundle = get_active_bundle(self.params)
+        self.sm.update(0)
+        self.chestnut_present = self.sm['deviceState'].chestnutPresent
+        self.source_models = {source: self.model_fetcher.get_bundles_for_source(source) for source in ModelFetcher.MODEL_SOURCES}
+        self.available_models = self.source_models[ModelFetcher.active_source(self.chestnut_present)]
+        validate_active_bundles(self.params, self.source_models)
+        self.active_bundle = get_active_bundle(self.params, chestnut=self.chestnut_present)

-        if (index_to_download := self.params.get("ModelManager_DownloadIndex")) is not None:
-          if self.active_bundle and self.active_bundle.index == index_to_download:
-            self.params.remove("ModelManager_DownloadIndex")
-          elif model_to_download := next((model for model in self.available_models if model.index == index_to_download), None):
-            try:
-              self.download(model_to_download, Paths.model_root())
-            except Exception as e:
-              cloudlog.exception(e)
-            finally:
-              self.params.remove("ModelManager_DownloadIndex")
-              self.selected_bundle = None
+        self._process_download_requests()

        if self.params.get("ModelManager_ClearCache"):
          self.clear_model_cache()
@@ -294,12 +346,14 @@ class ModelManagerSP:
    Clears the model cache directory of all files except those in the active model bundle.
    """

-    # Get list of files used by active model bundle
+    # Get list of files used by both slots' selected bundles (either may become
+    # the truly active bundle depending on hardware availability)
    active_files = []
-    if self.active_bundle is not None: # When the default model is active
-      for model in self.active_bundle.models:
-        if hasattr(model, 'artifact') and model.artifact.fileName:
-          active_files.append(model.artifact.fileName)
+    for source in ACTIVE_BUNDLE_KEYS:
+      if selected_bundle := get_selected_bundle(self.params, source):
+        for model in selected_bundle.models:
+          if model.artifact.fileName:
+            active_files.append(model.artifact.fileName)

    # Remove all files except active ones (including their chunk files)
    model_dir = Paths.model_root()
@@ -11,6 +11,7 @@ import http.server
 import os
 import tempfile
 import threading
+import time
 import unittest
 from typing import Any
 from unittest import mock
@@ -23,6 +24,10 @@ from openpilot.common.test import OpenpilotTestCase
 from openpilot.common.file_chunker import get_chunk_name, get_manifest_path
 from openpilot.selfdrive.test.helpers import http_server_context
 from openpilot.sunnypilot.models import manager as manager_module
+from openpilot.sunnypilot.models.fetcher import ModelFetcher, get_cached_bundles
+from openpilot.sunnypilot.models import helpers
+from openpilot.sunnypilot.models.helpers import (get_active_bundle, get_active_source, get_selected_bundle,
+                                                  resolve_bundle_by_ref, validate_active_bundles)
 from openpilot.sunnypilot.models.manager import ModelManagerSP

 CHUNK_BODIES = [b'A' * 5000, b'B' * 5000, b'C' * 3000]
@@ -98,11 +103,13 @@ class ManagerDownloadTestBase(OpenpilotTestCase):
    self.manager = ModelManagerSP.__new__(ModelManagerSP)
    self.manager.params = mock.MagicMock()
    self.manager.params.get.return_value = b'0'  # not cancelled
+    self.manager._download_ref = b'0'
    self.manager.pm = mock.MagicMock()
    self.manager.pm.send.side_effect = self._record_progress
    self.manager.selected_bundle = None
    self.manager.active_bundle = None
    self.manager.available_models = []
+    self.manager.chestnut_present = False
    self.manager._chunk_size = 1024
    self.manager._download_start_times = {}

@@ -249,6 +256,166 @@ class TestManagerDownload(ManagerDownloadTestBase):
        assert self.manager._download_start_times == {}
    self.run_with_server(body)

+  def test_download_ref_present_keeps_download_alive(self):
+    """A pending download request (DownloadRef set) must not be cancelled mid-transfer."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      self.manager.params.get.side_effect = lambda key: b"ref" if key == "ModelManager_DownloadRef" else None
+      self.manager._download_ref = b"ref"
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+      assert os.path.isfile(get_manifest_path(base_path))
+    self.run_with_server(body)
+
+  def test_cancellation_via_download_ref(self):
+    """Removing DownloadRef mid-transfer cancels the download."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      checks = {"n": 0}
+
+      def get(key):
+        if key == "ModelManager_DownloadRef":
+          checks["n"] += 1
+          return b"ref" if checks["n"] <= 2 else None
+        return b"0"
+
+      self.manager.params.get.side_effect = get
+      self.manager._download_ref = b"ref"
+      with self.assertRaises(Exception) as ctx:
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+      assert 'cancelled' in str(ctx.exception).lower()
+      assert not os.path.isfile(get_manifest_path(base_path))
+    self.run_with_server(body)
+
+  def test_replaced_download_ref_queues_instead_of_cancelling(self):
+    """Selecting another model mid-transfer lets the running download finish."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      self.manager.params.get.side_effect = lambda key: b"other-ref" if key == "ModelManager_DownloadRef" else None
+      self.manager._download_ref = b"ref"
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+      assert os.path.isfile(get_manifest_path(base_path))
+    self.run_with_server(body)
+
+  def test_replaced_download_ref_is_kept(self):
+    """A selection made during a download must survive that download's cleanup."""
+    self.manager.params.get.return_value = b"new-ref"
+    self.manager._download_ref = b"old-ref"
+    self.manager._release_download_ref()
+    self.manager.params.remove.assert_not_called()
+
+  def test_own_download_ref_is_released(self):
+    self.manager.params.get.return_value = b"ref"
+    self.manager._download_ref = b"ref"
+    self.manager._release_download_ref()
+    self.manager.params.remove.assert_called_once_with("ModelManager_DownloadRef")
+
+  def test_cached_bundle_cancel_skips_slot_write(self):
+    """A cancel must stop an already-on-disk bundle before it is applied to the slot."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      for i, data in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'wb') as f:
+          f.write(data)
+      self._bundle.ref = "test-ref"
+      params, store = self._make_params_with_store()
+      store["ModelManager_DownloadRef"] = None  # removed -> cancelled
+      self.manager.params = params
+      self.manager._download_ref = b"ref"
+      with self.assertRaises(Exception) as ctx:
+        asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "qcom"))
+      assert 'cancelled' in str(ctx.exception).lower()
+      assert "ModelManager_ActiveBundle" not in store
+      assert all(os.path.isfile(p) for p in self.chunk_paths(base_path)), "cancel must not delete cached chunks"
+    self.run_with_server(body)
+
+  def test_resume_skips_valid_chunks(self):
+    """A chunk already on disk is kept and not re-downloaded; progress starts above its share."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      with open(get_chunk_name(base_path, 0, len(CHUNK_BODIES)), 'wb') as f:
+        f.write(CHUNK_BODIES[0])
+
+      asyncio.run(self.manager._process_artifact(artifact, self.dest))
+
+      chunk0_suffix = get_chunk_name('', 0, len(CHUNK_BODIES))
+      assert not any(p.endswith(chunk0_suffix) for p in DownloadHandler.request_paths), "valid chunk was re-downloaded"
+      for i, expected in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'rb') as f:
+          assert f.read() == expected
+      assert os.path.isfile(get_manifest_path(base_path))
+      assert min(self.reported) >= (1 / len(CHUNK_BODIES)) * 100 - 1, "progress must not restart below the resumed share"
+    self.run_with_server(body)
+
+  def test_verify_reports_valid_fraction_then_cached(self):
+    """A fully cached bundle publishes climbing verify progress and ends cached."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      for i, data in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'wb') as f:
+          f.write(data)
+
+      asyncio.run(self.manager._process_artifact(artifact, self.dest))
+
+      assert DownloadHandler.request_paths == [], "cached bundle must not hit the network"
+      assert [round(p) for p in self.reported[:3]] == [33, 67, 100]
+      assert artifact.downloadProgress.status == custom.ModelManagerSP.DownloadStatus.cached
+    self.run_with_server(body)
+
+  def _make_params_with_store(self):
+    params = mock.MagicMock()
+    store = {}
+
+    def get(key, *args, **kwargs):
+      return store.get(key, b"0")  # b"0" -> download not cancelled
+
+    def put(key, value, *args, **kwargs):
+      store[key] = value
+
+    params.get.side_effect = get
+    params.put.side_effect = put
+    return params, store
+
+  def test_download_writes_qcom_slot(self):
+    """A download resolved to the qcom source writes the qcom active bundle slot only."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      self._bundle.ref = "test-ref"
+      self._bundle.minimumSelectorVersion = 18
+      params, store = self._make_params_with_store()
+      self.manager.params = params
+      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "qcom"))
+
+      assert "ModelManager_ActiveBundle" in store, "qcom download must write the qcom slot"
+      assert "ModelManager_ActiveBundleChestnut" not in store, "qcom download must not touch the chestnut slot"
+      assert self.manager.selected_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
+      assert self.manager.active_bundle is not None and self.manager.active_bundle.ref == "test-ref"
+      assert self.manager.active_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
+      chunk_names = [get_chunk_name(artifact.fileName, i, len(artifact.chunks)) for i in range(len(artifact.chunks))]
+      missing = [c for c in chunk_names if not os.path.isfile(os.path.join(self.dest, c))]
+      assert missing == [], f"chunks missing from the cache: {missing}"
+    self.run_with_server(body)
+
+  def test_download_writes_chestnut_slot(self):
+    """A download resolved to the chestnut source writes the chestnut active bundle slot only."""
+    def body():
+      self.make_artifact(chunked=True)
+      self._bundle.ref = "big-ref"
+      self._bundle.minimumSelectorVersion = 18
+      params, store = self._make_params_with_store()
+      self.manager.params = params
+      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "chestnut"))
+
+      assert "ModelManager_ActiveBundleChestnut" in store, "chestnut download must write the chestnut slot"
+      assert "ModelManager_ActiveBundle" not in store, "chestnut download must not touch the qcom slot"
+      assert self.manager.selected_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
+    self.run_with_server(body)
+

 class TestManagerImports(OpenpilotTestCase):
  """Catches undeclared dependencies. aiohttp lived only in the AGNOS venv; 19.6 dropped
@@ -267,6 +434,352 @@ class TestManagerImports(OpenpilotTestCase):
    assert connect > 0 and read > 0, "requests defaults to no timeout; downloads would hang forever"


+class TestResolveBundleByRef(OpenpilotTestCase):
+  """A ref resolves to (bundle, source) across both hardware manifests. Refs are
+  unique per manifest and never overlap across sources, so a ref maps to exactly
+  one slot. Shared by the manager's download flow and the settings UI."""
+
+  @staticmethod
+  def _bundle(ref: str):
+    bundle = custom.ModelManagerSP.ModelBundle.new_message()
+    bundle.ref = ref
+    return bundle
+
+  def test_qcom_ref_resolves_to_qcom_slot(self):
+    small = self._bundle("small")
+    assert resolve_bundle_by_ref("small", {"qcom": [small], "chestnut": []}) == (small, "qcom")
+
+  def test_chestnut_ref_resolves_to_chestnut_slot(self):
+    big = self._bundle("big")
+    assert resolve_bundle_by_ref("big", {"qcom": [], "chestnut": [big]}) == (big, "chestnut")
+
+  def test_unknown_ref_returns_none(self):
+    source_bundles = {"qcom": [self._bundle("small")], "chestnut": []}
+    assert resolve_bundle_by_ref("nope", source_bundles) is None
+
+
+def manifest_bundle(short_name: str, ref: str, index: int = 0, is_big: bool = False) -> dict:
+  """Minimal manifest bundle dict, version-compatible (no chunks to avoid disk side effects).
+  Big (chestnut) bundles carry `is_big: true` in the manifest JSON."""
+  return {
+    "index": index,
+    "short_name": short_name,
+    "display_name": short_name.upper(),
+    "generation": 1,
+    "environment": "release",
+    "runner": "tinygrad",
+    "is_big": is_big,
+    "minimum_selector_version": "18",
+    "ref": ref,
+    "models": [{
+      "type": "supercombo",
+      "artifact": {
+        "file_name": f"{short_name}.pkl",
+        "download_uri": {"url": f"https://example.com/{short_name}.pkl", "sha256": "s"},
+      },
+    }],
+  }
+
+
+def fresh_sync_time() -> int:
+  return int(time.monotonic() * 1e9)
+
+
+class TestModelFetcherSources(OpenpilotTestCase):
+  """Both manifests are always maintained: get_bundles_for_source exposes either
+  source by name, and active_source picks which one matches the attached hardware."""
+
+  def _make_params(self, qcom_manifest, chestnut_manifest):
+    params = mock.MagicMock()
+
+    def get(key):
+      if key == "ModelManager_ModelsCache":
+        return qcom_manifest
+      if key == "ModelManager_ModelsCache_Chestnut":
+        return chestnut_manifest
+      if key in ("ModelManager_LastSyncTime", "ModelManager_LastSyncTime_Chestnut"):
+        return fresh_sync_time()
+      return None
+
+    params.get.side_effect = get
+    return params
+
+  def test_active_source_follows_chestnut_presence(self):
+    assert ModelFetcher.active_source(False) == "qcom"
+    assert ModelFetcher.active_source(True) == "chestnut"
+
+  def test_get_bundles_for_source_returns_each_source(self):
+    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
+                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    assert [bundle.ref for bundle in fetcher.get_bundles_for_source("qcom")] == ["aaa"]
+    assert [bundle.ref for bundle in fetcher.get_bundles_for_source("chestnut")] == ["bbb"]
+
+  def test_get_bundles_for_source_unknown(self):
+    assert ModelFetcher(mock.MagicMock()).get_bundles_for_source("bogus") == []
+
+  def test_get_cached_bundles_parses_source(self):
+    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
+                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
+    qcom_bundles = get_cached_bundles(params, "qcom")
+    chestnut_bundles = get_cached_bundles(params, "chestnut")
+    assert [b.ref for b in qcom_bundles] == ["aaa"]
+    assert [b.ref for b in chestnut_bundles] == ["bbb"]
+    assert qcom_bundles[0].displayName == "SMALL"
+
+  def test_get_cached_bundles_empty_when_missing(self):
+    params = mock.MagicMock()
+    params.get.return_value = None
+    assert get_cached_bundles(params, "qcom") == []
+    assert get_cached_bundles(params, "chestnut") == []
+
+  def test_get_cached_bundles_unknown_source(self):
+    assert get_cached_bundles(mock.MagicMock(), "bogus") == []
+
+  def test_active_json_has_both_urls(self):
+    params = mock.MagicMock()
+    ModelFetcher(params)
+    active_json_calls = [call for call in params.put.call_args_list if call.args[0] == "ModelManager_ActiveJson"]
+    assert active_json_calls, "expected ModelManager_ActiveJson to be written"
+    assert active_json_calls[-1].args[1] == {
+      "qcom": ModelFetcher.MODEL_URL,
+      "chestnut": ModelFetcher.MODEL_URL_CHESTNUT,
+    }
+
+
+
+class TestSourceCacheIntegrity(OpenpilotTestCase):
+  """Each source's cached manifest must contain only that source's models; the
+  `is_big` flag in the JSON marks the big (chestnut) models. A mismatched cache is
+  legacy data from before the per-source split (the active manifest was cached
+  under the unsuffixed key regardless of hardware) and is refetched. This
+  replaces the old one-time bundle migration."""
+
+  def _make_params(self, qcom_manifest, chestnut_manifest):
+    params = mock.MagicMock()
+
+    def get(key):
+      if key == "ModelManager_ModelsCache":
+        return qcom_manifest
+      if key == "ModelManager_ModelsCache_Chestnut":
+        return chestnut_manifest
+      if key in ("ModelManager_LastSyncTime", "ModelManager_LastSyncTime_Chestnut"):
+        return fresh_sync_time()
+      return None
+
+    params.get.side_effect = get
+    return params
+
+  def _fetched(self, *bundles):
+    return ModelFetcher(mock.MagicMock()).model_parser.parse_models({"bundles": list(bundles)})
+
+  def test_qcom_cache_with_big_models_is_refetched(self):
+    """Legacy: the unsuffixed cache holds the big manifest. is_big confirms it is
+    the wrong set for qcom, so a fresh fetch replaces it."""
+    params = self._make_params({"bundles": [manifest_bundle("big", "bbb", is_big=True)]},
+                               {"bundles": [manifest_bundle("big2", "ccc", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    fetched = self._fetched(manifest_bundle("small", "aaa"))
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched):
+      bundles = fetcher.get_bundles_for_source("qcom")
+    assert [bundle.ref for bundle in bundles] == ["aaa"]
+
+  def test_chestnut_cache_without_big_models_is_refetched(self):
+    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
+                               {"bundles": [manifest_bundle("big2", "ccc")]})
+    fetcher = ModelFetcher(params)
+    fetched = self._fetched(manifest_bundle("big", "bbb", is_big=True))
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched):
+      bundles = fetcher.get_bundles_for_source("chestnut")
+    assert [bundle.ref for bundle in bundles] == ["bbb"]
+
+  def test_matching_caches_are_used_without_fetch(self):
+    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
+                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", side_effect=AssertionError("cache should be used")):
+      assert [bundle.ref for bundle in fetcher.get_bundles_for_source("qcom")] == ["aaa"]
+      assert [bundle.ref for bundle in fetcher.get_bundles_for_source("chestnut")] == ["bbb"]
+
+  def test_stale_version_cache_is_refetched(self):
+    """A source-matching cache whose bundles are all filtered by the selector version
+    check parses to zero valid bundles; it is stale (e.g. an old manifest) and must be
+    refetched instead of silently returning an empty list forever."""
+    stale = manifest_bundle("small", "aaa")
+    stale["minimum_selector_version"] = "16"
+    params = self._make_params({"bundles": [stale]},
+                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    fetched = self._fetched(manifest_bundle("small2", "ddd"))
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
+      bundles = fetcher.get_bundles_for_source("qcom")
+    fetch.assert_called_once_with("qcom")
+    assert [bundle.ref for bundle in bundles] == ["ddd"]
+
+  def test_mismatched_refetch_happens_once(self):
+    """If the fresh manifest still fails the source check, the URL is authoritative:
+    trust it instead of refetching at 1 Hz forever."""
+    params = self._make_params({"bundles": [manifest_bundle("big", "bbb", is_big=True)]},
+                               {"bundles": [manifest_bundle("big2", "ccc", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    fetched = self._fetched(manifest_bundle("big", "bbb", is_big=True))
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
+      first = fetcher.get_bundles_for_source("qcom")
+      second = fetcher.get_bundles_for_source("qcom")
+    fetch.assert_called_once_with("qcom")
+    assert [bundle.ref for bundle in first] == ["bbb"]
+    assert [bundle.ref for bundle in second] == ["bbb"]
+
+  def test_corrupt_cache_is_refetched(self):
+    """A cache that fails to parse (e.g. truncated/foreign JSON) must trigger a
+    refetch instead of raising every loop and never recovering."""
+    corrupt = {"bundles": [{"short_name": "broken"}]}  # missing required fields
+    params = self._make_params(corrupt, {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
+    fetcher = ModelFetcher(params)
+    fetched = self._fetched(manifest_bundle("small", "aaa"))
+    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
+      bundles = fetcher.get_bundles_for_source("qcom")
+    fetch.assert_called_once_with("qcom")
+    assert [bundle.ref for bundle in bundles] == ["aaa"]
+
+
+class TestActiveBundleValidation(OpenpilotTestCase):
+  """Validation is per-slot: a failed fetch (empty bundle list) must not reset a slot,
+  and resetting one slot must not stomp the runner cache derived from the other."""
+
+  def setUp(self):
+    super().setUp()
+    helpers._LAST_VALIDATED_RAW.clear()
+
+  @staticmethod
+  def _raw_bundle(ref: str, runner: int | None = None) -> dict:
+    bundle = custom.ModelManagerSP.ModelBundle.new_message()
+    bundle.ref = ref
+    bundle.minimumSelectorVersion = 18
+    if runner is not None:
+      bundle.runner = runner
+    return bundle.to_dict()
+
+  def _params(self, qcom=None, chestnut=None):
+    params = mock.MagicMock()
+
+    def get(key, *args, **kwargs):
+      return {"ModelManager_ActiveBundle": qcom, "ModelManager_ActiveBundleChestnut": chestnut}.get(key)
+
+    params.get.side_effect = get
+    return params
+
+  def test_empty_catalog_does_not_reset_slot(self):
+    params = self._params(qcom=self._raw_bundle("small"))
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=False):
+      validate_active_bundles(params, {"qcom": [], "chestnut": []})
+    params.remove.assert_not_called()
+
+  def test_reset_recomputes_runner_from_surviving_slot(self):
+    tinygrad = int(custom.ModelManagerSP.Runner.tinygrad)
+    big_raw = self._raw_bundle("big", runner=tinygrad)
+    params = self._params(qcom=self._raw_bundle("gone"), chestnut=big_raw)
+    catalog = {"qcom": [custom.ModelManagerSP.ModelBundle(**self._raw_bundle("other"))],
+               "chestnut": [custom.ModelManagerSP.ModelBundle(**big_raw)]}
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=True):
+      validate_active_bundles(params, catalog)
+    params.remove.assert_called_once_with("ModelManager_ActiveBundle")
+    runner_puts = [call for call in params.put.call_args_list if call.args[0] == "ModelRunnerTypeCache"]
+    assert [call.args[1] for call in runner_puts] == [tinygrad]
+
+
+class TestActiveBundleSelection(OpenpilotTestCase):
+  """The effective active bundle is the active source's slot: chestnut when a GPU is
+  present, qcom otherwise. An empty active slot means the hardware default (stock
+  runner), never the other slot's pick - modeld_v2 requires a real bundle."""
+
+  @staticmethod
+  def _raw_bundle(ref: str) -> dict:
+    bundle = custom.ModelManagerSP.ModelBundle.new_message()
+    bundle.ref = ref
+    bundle.minimumSelectorVersion = 18
+    return bundle.to_dict()
+
+  def _params(self, qcom=None, chestnut=None):
+    params = mock.MagicMock()
+
+    def get(key, *args, **kwargs):
+      if key == "ModelManager_ActiveBundle":
+        return qcom
+      if key == "ModelManager_ActiveBundleChestnut":
+        return chestnut
+      return None
+
+    params.get.side_effect = get
+    return params
+
+  def test_selected_bundle_is_per_slot(self):
+    params = self._params(qcom=self._raw_bundle("small"), chestnut=self._raw_bundle("big"))
+    assert get_selected_bundle(params, "qcom").ref == "small"
+    assert get_selected_bundle(params, "chestnut").ref == "big"
+
+  def test_no_gpu_uses_qcom_slot(self):
+    params = self._params(qcom=self._raw_bundle("small"), chestnut=self._raw_bundle("big"))
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=False):
+      assert get_active_bundle(params).ref == "small"
+
+  def test_gpu_uses_chestnut_slot(self):
+    params = self._params(qcom=self._raw_bundle("small"), chestnut=self._raw_bundle("big"))
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=True):
+      assert get_active_bundle(params).ref == "big"
+
+  def test_gpu_without_big_selection_is_hardware_default(self):
+    params = self._params(qcom=self._raw_bundle("small"), chestnut=None)
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=True):
+      assert get_active_bundle(params) is None
+
+
+class TestEffectiveSource(OpenpilotTestCase):
+  """One gate decides the active source. With no flags it is runtime truth (GPU
+  attached); display callers (mici) pass the ui_state flags, which additionally
+  require the big model to be loading, active, or the device offroad. The active
+  bundle is simply the selected bundle of that source."""
+
+  @staticmethod
+  def _raw_bundle(ref: str) -> dict:
+    bundle = custom.ModelManagerSP.ModelBundle.new_message()
+    bundle.ref = ref
+    bundle.minimumSelectorVersion = 18
+    return bundle.to_dict()
+
+  def test_runtime_no_gpu(self):
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=False):
+      assert get_active_source() == "qcom"
+
+  def test_runtime_gpu_present(self):
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=True):
+      assert get_active_source() == "chestnut"
+
+  def test_display_offroad_gpu_present_shows_big(self):
+    assert get_active_source(chestnut=True, chestnut_active=False, chestnut_loading=False, offroad=True) == "chestnut"
+
+  def test_display_onroad_gpu_loading_shows_big(self):
+    assert get_active_source(chestnut=True, chestnut_active=False, chestnut_loading=True, offroad=False) == "chestnut"
+
+  def test_display_onroad_gpu_active_shows_big(self):
+    assert get_active_source(chestnut=True, chestnut_active=True, chestnut_loading=False, offroad=False) == "chestnut"
+
+  def test_display_onroad_gpu_idle_shows_small(self):
+    assert get_active_source(chestnut=True, chestnut_active=False, chestnut_loading=False, offroad=False) == "qcom"
+
+  def test_display_active_none_is_idle(self):
+    assert get_active_source(chestnut=True, chestnut_active=None, chestnut_loading=False, offroad=False) == "qcom"
+
+  def test_active_bundle_follows_source(self):
+    params = mock.MagicMock()
+    params.get.side_effect = lambda key: {"ModelManager_ActiveBundle": self._raw_bundle("small"),
+                                          "ModelManager_ActiveBundleChestnut": self._raw_bundle("big")}.get(key)
+    with mock.patch("openpilot.sunnypilot.models.helpers.chestnut_present", return_value=False):
+      assert get_active_bundle(params).ref == "small"
+    assert get_selected_bundle(params, get_active_source(chestnut=True, chestnut_active=False,
+                                                         chestnut_loading=False, offroad=True)).ref == "big"
+
+
@unittest.skipUnless(os.environ.get('RUN_INTEGRATION_TESTS'), 'requires external network')
 class TestLiveModelManifest(OpenpilotTestCase):
  """Every artifact and chunk URL in the published manifest must resolve."""
@@ -1,13 +1,11 @@
 import requests

-from openpilot.common.params import Params
 from openpilot.sunnypilot.models.tinygrad_ref import get_tinygrad_ref
 from openpilot.sunnypilot.models.fetcher import ModelFetcher
 from openpilot.common.test import OpenpilotTestCase

 def fetch_tinygrad_ref():
-  fetcher = ModelFetcher(Params())
-  response = requests.get(fetcher.model_url, timeout=10)
+  response = requests.get(ModelFetcher.MODEL_URL, timeout=10)
  response.raise_for_status()
  json_data = response.json()
  return json_data.get("tinygrad_ref")
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:447099e93e303b29e7b3eac237bb0f27f8c5e12786991139aee2432532a75f58
+size 12310
@@ -252,4 +252,12 @@ EVENTS_SP: dict[int, dict[str, Alert | AlertCallbackType]] = {
      AlertStatus.userPrompt, AlertSize.small,
      Priority.LOW, VisualAlert.none, AudibleAlert.prompt, 0.1),
  },
+
+  EventNameSP.bigModelReady: {
+    ET.PERMANENT: Alert(
+      "Big Model Ready",
+      "",
+      AlertStatus.normal, AlertSize.small,
+      Priority.LOW, VisualAlert.none, AudibleAlert.prompt, 2.),
+  },
 }
@@ -28,7 +28,6 @@ from websocket import (ABNF, WebSocket, WebSocketException, WebSocketTimeoutExce
                       create_connection, WebSocketConnectionClosedException)

 import openpilot.cereal.messaging as messaging
-from openpilot.selfdrive.modeld.helpers import usbgpu_present
 from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL, DEFAULT_BIG_MODEL
 from openpilot.sunnypilot.selfdrive.car.sync_sunnylink_params import update_car_list_param
 from openpilot.sunnypilot.sunnylink.api import SunnylinkApi
@@ -182,11 +181,9 @@ def getParamsMetadata() -> str:
    schema = generate_schema()
    schema["capabilities"] = generate_capabilities()
    schema["capability_labels"] = CAPABILITY_LABELS
-    # mirrors get_default_model() — ui_state unavailable in sunnylinkd process
-    show_big = (usbgpu_present()
-                and (params.get_bool("UsbGpuActive") or params.get_bool("UsbGpuLoading") or params.get_bool("IsOffroad")))
-    schema["default_model"] = DEFAULT_BIG_MODEL if show_big else DEFAULT_MODEL
-    schema["usbgpu_active"] = params.get_bool("UsbGpuActive")
+    schema["default_model"] = DEFAULT_MODEL
+    schema["default_big_model"] = DEFAULT_BIG_MODEL
+    schema["chestnut_active"] = params.get_bool("ChestnutActive")
    raw = json.dumps(schema, separators=(",", ":")).encode("utf-8")
    return base64.b64encode(gzip.compress(raw)).decode("utf-8")
  except Exception:
@@ -65,6 +65,7 @@ def sp_stats(end_event):
    'MadsSteeringMode',
    'MadsUnifiedEngagementMode',
    'ModelManager_ActiveBundle',
+    'ModelManager_ActiveBundleChestnut',
    'ModelManager_Favs',
    'EnableSunnylinkUploader',
    'SunnylinkEnabled',
@@ -84,6 +84,25 @@ def _migrate_tesla_mads_screen_button(_params):
    cloudlog.exception(f"Error migrating TeslaMadsScreenButton: {e}")


+def _migrate_model_bundle_slots(_params):
+  # Pre-split, a chestnut user's big-model selection lived in the single
+  # ActiveBundle. Seed both slots; validation drops whichever does not match
+  # its own manifest.
+  try:
+    if _params.get("ModelManager_ActiveBundleChestnut") is not None:
+      return
+    if (chestnut_bundle := _params.get("ModelManager_ActiveBundleUSBGPU")) is not None:
+      _params.put("ModelManager_ActiveBundleChestnut", chestnut_bundle, block=True)
+      cloudlog.info("params_migration: seeded ModelManager_ActiveBundleChestnut from ModelManager_ActiveBundleUSBGPU")
+      return
+    if (bundle := _params.get("ModelManager_ActiveBundle")) is None:
+      return
+    _params.put("ModelManager_ActiveBundleChestnut", bundle, block=True)
+    cloudlog.info("params_migration: seeded ModelManager_ActiveBundleChestnut from ModelManager_ActiveBundle")
+  except Exception as e:
+    cloudlog.exception(f"Error migrating model bundle slots: {e}")
+
+
 def run_migration(_params):
  # migrate OnroadScreenOffBrightness
  if _params.get("OnroadScreenOffBrightnessMigrated") != ONROAD_BRIGHTNESS_MIGRATION_VERSION:
@@ -120,3 +139,6 @@ def run_migration(_params):

  # seed TeslaMadsScreenButton for existing Tesla installs
  _migrate_tesla_mads_screen_button(_params)
+
+  # seed the chestnut model slot from the pre-split single slot
+  _migrate_model_bundle_slots(_params)
@@ -0,0 +1,36 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.common.params import Params
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.system.params_migration import _migrate_model_bundle_slots
+
+
+class TestModelBundleSlotMigration(OpenpilotTestCase):
+  """Pre-split, a chestnut user's big-model selection lived in the single ActiveBundle.
+  The migration seeds both slots; per-source validation later drops whichever does not
+  match its own manifest."""
+
+  def test_seeds_chestnut_slot_from_active_bundle(self):
+    params = Params()
+    bundle = {"ref": "big", "minimumSelectorVersion": 18}
+    params.put("ModelManager_ActiveBundle", bundle, block=True)
+    _migrate_model_bundle_slots(params)
+    assert params.get("ModelManager_ActiveBundleChestnut") == bundle
+    assert params.get("ModelManager_ActiveBundle") == bundle
+
+  def test_noop_when_chestnut_slot_already_set(self):
+    params = Params()
+    params.put("ModelManager_ActiveBundle", {"ref": "small"}, block=True)
+    params.put("ModelManager_ActiveBundleChestnut", {"ref": "big"}, block=True)
+    _migrate_model_bundle_slots(params)
+    assert params.get("ModelManager_ActiveBundleChestnut") == {"ref": "big"}
+
+  def test_noop_when_no_selection(self):
+    params = Params()
+    _migrate_model_bundle_slots(params)
+    assert params.get("ModelManager_ActiveBundleChestnut") is None
@@ -16,7 +16,7 @@ from openpilot.common.utils import strip_deprecated_keys
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.params import Params
 from openpilot.common.realtime import DT_HW
-from openpilot.selfdrive.modeld.helpers import MODELS_DIR, usbgpu_compiled
+from openpilot.selfdrive.modeld.helpers import MODELS_DIR, chestnut_compiled
 from openpilot.selfdrive.selfdrived.alertmanager import set_offroad_alert
 from openpilot.common.hardware import HARDWARE, COMMA_HARDWARE
 from openpilot.common.basedir import BASEDIR
@@ -239,7 +239,7 @@ def hardware_thread(end_event, hw_queue) -> None:

  fan_controller = FanController(int(1./DT_HW))
  chestnut = Chestnut()
-  big_model_available = (MODELS_DIR / 'big_driving_supercombo.onnx').is_file() or usbgpu_compiled()
+  big_model_available = (MODELS_DIR / 'big_driving_supercombo.onnx').is_file() or chestnut_compiled()

  while not end_event.is_set():
    sm.update(PANDA_STATES_TIMEOUT)
@@ -8,12 +8,26 @@ from collections.abc import Callable

 import pyray as rl

-from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.sunnypilot.lib.styles import style
 from openpilot.system.ui.sunnypilot.widgets.list_view import ButtonActionSP
-from openpilot.system.ui.widgets.label import UnifiedLabel
+from openpilot.system.ui.widgets.label import ScrollState, UnifiedLabel
 from openpilot.system.ui.widgets.list_view import BUTTON_WIDTH, BUTTON_HEIGHT, TEXT_PADDING, _resolve_value

+SCROLL_SPEED = 1.2  # stock is 0.8, boosted 50% to compensate for larger font (50 vs 32)
+SCROLL_REFERENCE_FPS = 60.
+
+
+class UnifiedLabelSP(UnifiedLabel):
+  # stock scroll formula (0.8 / 60 * fps) is inverted — pre-correct so speed is constant px/sec
+  def _render(self, _):
+    if self._needs_scroll and self._scroll_state == ScrollState.SCROLLING:
+      fps = gui_app.target_fps
+      wrong_step = 0.8 / SCROLL_REFERENCE_FPS * fps
+      correct_step = SCROLL_SPEED * SCROLL_REFERENCE_FPS / fps
+      self._scroll_offset -= (correct_step - wrong_step)
+    super()._render(_)
+

 class NoElideButtonAction(ButtonActionSP):
  def get_width_hint(self):
@@ -21,14 +35,12 @@ class NoElideButtonAction(ButtonActionSP):


 class ScrollingButtonAction(ButtonActionSP):
-  """ButtonActionSP whose value scrolls instead of eliding when it doesn't fit."""
-
  def __init__(self, text: str | Callable[[], str], width: int = style.BUTTON_ACTION_WIDTH,
               enabled: bool | Callable[[], bool] = True):
    super().__init__(text=text, width=width, enabled=enabled)
-    self._value_label = UnifiedLabel("", font_size=style.ITEM_TEXT_FONT_SIZE, font_weight=FontWeight.NORMAL,
-                                     text_color=self._value_color, scroll=True,
-                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+    self._value_label = UnifiedLabelSP("", font_size=style.ITEM_TEXT_FONT_SIZE, font_weight=FontWeight.NORMAL,
+                                       text_color=self._value_color, scroll=True,
+                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)

  def set_value(self, value: str | Callable[[], str], color: rl.Color = style.ITEM_TEXT_VALUE_COLOR):
    if self.value != _resolve_value(value, ""):
@@ -16,6 +16,7 @@ from openpilot.system.ui.lib.text_measure import measure_text_cached
 from openpilot.system.ui.sunnypilot.lib.styles import style
 from openpilot.system.ui.sunnypilot.widgets.list_view import ListItemSP
 from openpilot.system.ui.widgets.label import UnifiedLabel
+from openpilot.system.ui.sunnypilot.lib.utils import UnifiedLabelSP
 from openpilot.system.ui.widgets.list_view import ItemAction

 FONT_SIZE = style.ITEM_TEXT_FONT_SIZE
@@ -24,6 +25,8 @@ ICON_PADDING = 12

 BAR_WIDTH = 1100
 BAR_HEIGHT = 20
+SEGMENT_GAP = 24
+SEGMENT_NAME_MAX_WIDTH = 380
 BAR_GAP = 16
 BAR_RADIUS = BAR_HEIGHT / 2
 CAPSULE_POINTS = 24
@@ -45,6 +48,8 @@ class DownloadStatusAction(ItemAction):
    super().__init__(width=BAR_WIDTH)
    self.name = ""
    self.status_text = ""
+    self.segments: list[tuple[str, rl.Color, str | None, rl.Color | None]] | None = None
+    self._segment_labels: list[UnifiedLabelSP] = []
    self.downloading = False
    self.text_color = rl.GRAY
    self.icon: str | None = None
@@ -62,7 +67,8 @@ class DownloadStatusAction(ItemAction):
                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)

-  def update(self, name, downloading=False, progress=0.0, status_text="", text_color=rl.GRAY, icon=None, icon_color=None):
+  def update(self, name, downloading=False, progress=0.0, status_text="", text_color=rl.GRAY, icon=None, icon_color=None, segments=None):
+    self.segments = segments
    if downloading and not self.downloading:
      self._name_label.reset_shimmer()
      self._progress.x = progress
@@ -85,11 +91,22 @@ class DownloadStatusAction(ItemAction):
  def get_width_hint(self) -> float:
    if self.downloading:
      return BAR_WIDTH
+    if self.segments:
+      return sum(total for _, _, total in self._measured_segments())
    width = measure_text_cached(self._font, self._idle_text, FONT_SIZE).x
    if self.icon:
      width += ICON_SIZE + ICON_PADDING
    return width

+  def _measured_segments(self):
+    """[(segment, text width, total width incl. icon and gap)]"""
+    out = []
+    for i, seg in enumerate(self.segments or []):
+      text_width = min(measure_text_cached(self._font, seg[0], FONT_SIZE).x, SEGMENT_NAME_MAX_WIDTH)
+      total = text_width + (ICON_PADDING + ICON_SIZE if seg[2] else 0) + (SEGMENT_GAP if i else 0)
+      out.append((seg, text_width, total))
+    return out
+
  def _render(self, rect: rl.Rectangle):
    if self.downloading:
      self._render_downloading(rect)
@@ -134,6 +151,8 @@ class DownloadStatusAction(ItemAction):

  def _render_downloading(self, rect: rl.Rectangle):
    percent = f"{int(self._progress.x)}%"
+    if self.status_text:
+      percent = f"{self.status_text} {percent}"
    text_height = measure_text_cached(self._font, percent, FONT_SIZE).y
    top = rect.y + (rect.height - (text_height + BAR_GAP + BAR_HEIGHT)) / 2

@@ -148,6 +167,9 @@ class DownloadStatusAction(ItemAction):
    self._draw_fill(rail, max(0.0, min(rect.width, rect.width * (self._progress.x / 100.0))))

  def _render_idle(self, rect: rl.Rectangle):
+    if self.segments:
+      self._render_segments(rect)
+      return
    text = self._idle_text
    text_size = measure_text_cached(self._font, text, FONT_SIZE)
    right = rect.x + rect.width
@@ -161,6 +183,29 @@ class DownloadStatusAction(ItemAction):
    rl.draw_text_ex(self._font, text, rl.Vector2(right - text_size.x, rect.y + (rect.height - text_size.y) / 2),
                    FONT_SIZE, 0, self.text_color)

+  def _render_segments(self, rect: rl.Rectangle):
+    measured = self._measured_segments()
+    while len(self._segment_labels) < len(measured):
+      self._segment_labels.append(UnifiedLabelSP("", font_size=FONT_SIZE, max_width=SEGMENT_NAME_MAX_WIDTH,
+                                                 scroll=True, wrap_text=False))
+    x = rect.x + rect.width - sum(total for _, _, total in measured)
+    for i, ((text, color, icon, icon_color), text_width, _) in enumerate(measured):
+      if i:
+        x += SEGMENT_GAP
+      label = self._segment_labels[i]
+      if label.text != text:
+        label.set_text(text)
+      label.set_text_color(color)
+      text_height = measure_text_cached(self._font, text, FONT_SIZE).y
+      label.set_position(x, rect.y + (rect.height - text_height) / 2)
+      label.render()
+      x += text_width
+      if icon:
+        texture = gui_app.texture(icon, ICON_SIZE, ICON_SIZE, keep_aspect_ratio=True)
+        rl.draw_texture_v(texture, rl.Vector2(x + ICON_PADDING, rect.y + (rect.height - texture.height) / 2),
+                          icon_color or color)
+        x += ICON_PADDING + ICON_SIZE
+

 def download_status_item(title):
  return ListItemSP(title=title, action_item=DownloadStatusAction(), title_color=style.ITEM_TEXT_COLOR)
@@ -136,7 +136,7 @@ def generate_chunked_model(driving_pkl: Path) -> dict:


 def create_metadata_json(models: list, output_dir: Path, custom_name=None, short_name=None, is_20hz=False, upstream_branch="unknown",
-                         onnx_sha256=None) -> None:
+                         onnx_sha256=None, is_big=False) -> None:
  bundle_json = {
    "short_name": short_name,
    "display_name": custom_name or upstream_branch,
@@ -149,6 +149,7 @@ def create_metadata_json(models: list, output_dir: Path, custom_name=None, short
    "generation": "-1",
    "build_time": datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ"),
    "overrides": {},
+    "is_big": is_big,
    "models": models,
  }

@@ -186,6 +187,8 @@ if __name__ == "__main__":
    print(f"No driving_tinygrad.pkl found in {_output_dir}", file=sys.stderr)
    sys.exit(1)

+  is_big = _driving_pkl.name.startswith('big_')
+
  if _pkl:
    new_pkl = _output_dir / f"driving_{_pkl}_tinygrad.pkl"
    if not new_pkl.exists():
@@ -196,4 +199,4 @@ if __name__ == "__main__":
  _model_metadata = generate_chunked_model(_driving_pkl)
  _onnx_sha256 = _hash_onnx_files(Path(args.model_dir))
  create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch,
-                       onnx_sha256=_onnx_sha256)
+                       onnx_sha256=_onnx_sha256, is_big=is_big)
@@ -47,7 +47,7 @@ git rm -rf $OUTPUT_DIR/.git || true # Doing cleanup, but it might fail if the .g
 git remote remove origin || true # ensure cleanup
 git remote add origin $GIT_ORIGIN
 #git push origin -d $DEV_BRANCH || true # Ensuring we delete the remote branch if it exists as we are wiping it out
-git fetch origin $DEV_BRANCH || (git checkout -b $DEV_BRANCH && git commit --allow-empty -m "sunnypilot v$VERSION release" && git push -u origin $DEV_BRANCH)
+git fetch --depth 1 origin $DEV_BRANCH || (git checkout -b $DEV_BRANCH && git commit --allow-empty -m "sunnypilot v$VERSION release" && git push -u origin $DEV_BRANCH)

 echo "[-] committing version $VERSION T=$SECONDS"
 git add -f .
@@ -93,14 +93,11 @@ wheels = [

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+version = "8.5.0"
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-dependencies = [
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-]
-sdist = { url = "https://files.pythonhosted.org/packages/76/d4/81420972a676e8ffea40450d8c8c92943e7218a78fe9b64359836cc9876b/click-8.4.2.tar.gz", hash = "sha256:9a6cea6e60b17ebe0a44c5cc636d94f09bd66142c1cd7d8b4cd731c4917a15f6", size = 338000, upload-time = "2026-06-24T17:45:15.148Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c7/0e/7fa0ef50764b67090eca4114772a2abf8b6148198475e54c660b97caeee6/click-8.5.0.tar.gz", hash = "sha256:ba0d2089de75ea0310e2dde03160e6ca10009947fb95a182f9b54021bb272e34", size = 382235, upload-time = "2026-08-26T13:33:14.56Z" }
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+    { url = "https://files.pythonhosted.org/packages/58/50/6c0d534c5f134586a8e1ba4e330569e32f057e33372ae556463212fb4cd3/click-8.5.0-py3-none-any.whl", hash = "sha256:255bc9599cf7748b4b1a446ccc735421bd08a2ae529a8b88597d3de5664ee360", size = 125251, upload-time = "2026-08-26T13:33:12.928Z" },
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 [[package]]
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+version = "0.2.2.post101"
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 [[package]]
Author	SHA1	Message	Date
github-actions[bot]	c45ca0538f	Update Python packages	2026-08-31 19:57:02 +00:00
royjr	de197ba6fa	chestnut: alert when big model ready (#1947 ) egpu: alert when big model ready Co-authored-by: Jason Wen <haibin.wen3@gmail.com>	2026-08-30 16:20:16 -04:00
Jason Wen	1dd5a7c91d	Sync: `commaai/openpilot:master` → `sunnypilot/sunnypilot:master` (#1973 )	2026-08-28 12:58:26 -04:00
nayan	acb784d207	Merge commit '4a13639cfd122ccb9113a4d6ce225dcbd8e61914' into sync-20260827 # Conflicts: # openpilot/selfdrive/modeld/SConscript # openpilot/selfdrive/modeld/modeld.py # openpilot/selfdrive/ui/mici/layouts/home.py # openpilot/selfdrive/ui/ui_state.py # tinygrad_repo	2026-08-28 12:39:53 -04:00
Nayan	4075befc5e	osm: support map deletion via sunnylink (#1971 ) delete delete	2026-08-27 11:23:26 -04:00
Jason Wen	9f43d2477d	[MICI] ui: move and restyle the sunnylink pill in settings (#1972 )	2026-08-27 03:52:57 -04:00
Nayan	2d6cc4c065	models: Model Selector upgrades (#1953 ) * uh, i did not commit anything all this time * slideee to the left, cha cha * lint lint * ui: unify model source predicate and per-source bundle lookup in model_info * [TIZI/TICI] ui: disable the other-model row onroad like the active row * [TIZI/TICI] ui: drop docstring that restates the function name * [TIZI/TICI] ui: keep Favorites as the first model folder in the picker * ui: record why model names read the params slots and not modelManagerSP * ui: show the default model's name on the picker Default entries * models: bind a download to its ref so cancel and reselect work everywhere * models: resume partial chunked downloads and verify silently * models: publish a verifying status so cached checks read as verification, not a stuck download * [TIZI/TICI] ui: move download status onto each model's own row * [TIZI/TICI] ui: show the row status description while it has text * [TIZI/TICI] ui: restore the Model Status bar row * models: a cancel interrupts verification immediately and keeps on-disk chunks * models: a selection made mid-download queues instead of cancelling the transfer * [TIZI/TICI] ui: Model Status shows both slots idle and the queued pick while busy * [TIZI/TICI] ui: label the Model Status slots small and big and scroll long names * models: start a queued download in the same tick and label empty slots (Default) * ui: scroll Model Status names at the corrected speed * [TIZI/TICI] ui: Model Status shows the big model failing over to small * [TIZI/TICI] ui: stable model rows and a runner-matched failover note on Model Status * [TIZI/TICI] ui: model rows show full names and the failover note reopens with the page * ui: name the actually driving model runner-matched and bring mici to state parity * fix ugly --------- Co-authored-by: Jason Wen <haibin.wen3@gmail.com> Co-authored-by: James Vecellio-Grant <159560811+Discountchubbs@users.noreply.github.com>	2026-08-27 02:03:53 -04:00
Daniel Koepping	4a13639cfd	reduce chestnut states (#38705 ) ui: unify chestnut status presentation	2026-08-26 19:12:49 -07:00
YassineYousfi	fa75fdd852	chestnut stats: overlap with gpu work (#38704 ) * chestnut stats: overlap with gpu work * ci --------- Co-authored-by: elkoled <elkoled@gmail.com>	2026-08-26 17:57:55 -07:00
Daniel Koepping	5cfdb2f4da	rename usbgpu to chestnut (#38703 ) chestnut: rename eGPU interfaces	2026-08-26 15:42:59 -07:00
Daniel Koepping	63548ce10d	bump tinygrad (#38702 )	2026-08-26 15:20:04 -07:00
Daniel Koepping	980fb79c1a	update orange GPU icon (#38701 ) mici: update failed eGPU icon	2026-08-26 12:21:14 -07:00
Harald Schäfer	d40df6f829	modeld: fall back on invalid big model outputs (#38700 )	2026-08-26 12:06:53 -07:00
Nayan	da28afca91	models: dual-slot backend (qcom/usbgpu) with ref-based downloads (#1966 ) * models: dual-slot backend (qcom/usbgpu) with ref-based downloads * models: restore get_active_source and the usbgpu-to-qcom fallback * models: fix per-slot validation and cap mismatched-source refetches * ui/models: select models by ref and seed the usbgpu slot on migration * models: drop defensive attribute guards on capnp bundles * models: remove vestigial fetcher state and dead fallbacks * models: resolve the active bundle from the active source slot only * models: pass the usbgpu kwarg through the modeld test stubs * models: resolve the displayed model from the active slot in ui_state * models: correct the validation memo type hint * models: drop docstrings that restate the function name --------- Co-authored-by: Jason Wen <haibin.wen3@gmail.com>	2026-08-26 02:34:02 -04:00
Jason Wen	15f201caed	ui: use full big model failure detection for sidebar and home eGPU icons (#1969 )	2026-08-25 21:07:44 -04:00
Jason Wen	1d4558c067	[TIZI/TICI] sidebar: show eGPU icon when chestnut is present (#1968 ) * [tizi/tici] sidebar: show eGPU icon when chestnut is present * matchy match * fix	2026-08-25 20:47:52 -04:00
Jason Wen	78a766eb61	ui: fix scrolling label speed at non-60fps refresh rates (#1967 ) * ui: fix scrolling label speed at non-60fps refresh rates * send it * nope * more	2026-08-25 20:38:02 -04:00
Jason Wen	b742b96c44	[MICI] ui: four-state eGPU icon for non-default big models (#1945 ) * ui: four-state eGPU icon for non-default big models * oops * try this out * align	2026-08-25 12:04:39 -04:00
Jason Wen	25c25047b8	models: persist model selection per catalog across chestnut state changes (#1960 )	2026-08-25 01:12:12 -04:00
Jason Wen	cefe5737b9	models: fix current model not updating on chestnut status (#1959 ) * models: preserve user model selection across reboots and power cycles * no * again * idk * over	2026-08-25 00:41:31 -04:00
Jason Wen	760c19d3f9	ui/models: handle missing files during cache size calculation (#1958 )	2026-08-24 23:31:52 -04:00
James Vecellio-Grant	45814e3313	modeld_v2: spatial features (#1934 ) * modeld_v2: spatial features * Update fetcher.py * dont reshape non 4 dim arrays * realize for non compiled * Update compile_modeld.py * god dammit it was realize() * it was fucking frozen tinygrad. just need to recompile * bump * ci: add is_big flag to metadata.json to support backward compat * Update model_generator.py * Update sunnypilot-build-model.yaml * Update helpers.py * Revert "Update helpers.py" This reverts commit `3a955ca11a`. * Reapply "Update helpers.py" This reverts commit `ca9c6e1933`. * models: use less strict chestnut detection state --------- Co-authored-by: Jason Wen <haibin.wen3@gmail.com>	2026-08-24 22:52:29 -04:00
Jason Wen	2ba91d2be5	ci: add tinygrad ref check to prepare_chestnut and even faster prebuilt stages (#1957 ) * ci: faster prebuilt stages * tg check chestnut * zoomer!	2026-08-24 22:42:45 -04:00
Jason Wen	19f83b274f	ci: identical environment for publish_chestnut prebuilt	2026-08-24 22:06:20 -04:00
Jason Wen	d14d0b1dd0	ci: parallelize models chunk downloads and split branch publishing (#1955 ) * ci: parallelize model chunk downloads and better publish * ci: download all model chunks in parallel with xargs -P8 * split split * ew * must require	2026-08-24 21:48:53 -04:00
Jason Wen	6cc5f3aad8	ci: fix DM model build, separate HF defaults paths, nuke build races (#1956 ) * ci: fix DM model build, separate HF defaults paths, nuke build races * more split! * name * ci: download driving and DM model chunks into chestnut prebuilt output	2026-08-24 20:02:48 -04:00
Jason Wen	8e16c9babb	ci: offload small model compilation (#1952 ) * ci: compile default big model with stock modeld * Revert "Revert big RL model (#38627)" This reverts commit `516ec1e682`. * ci: compile default small model with stock modeld compiler * ci: offload small model compilation * Reapply "Revert big RL model (#38627)" This reverts commit `d06cfabb62`. * Reapply "Revert big RL model (#38627)" This reverts commit `d06cfabb62`.	2026-08-24 16:24:19 -04:00
Jason Wen	2bcfed5c71	ci: compile default models with stock modeld (#1954 ) * ci: compile default big model with stock modeld * Revert "Revert big RL model (#38627)" This reverts commit `516ec1e682`. * ci: compile default small model with stock modeld compiler * Reapply "Revert big RL model (#38627)" This reverts commit `d06cfabb62`.	2026-08-24 15:37:46 -04:00
Jason Wen	66cf334067	ci: unify default model build into single workflow (#1951 ) * ci: unify default model build into single workflow * ci: consolidate upload jobs and add tinygrad ref validation	2026-08-24 12:35:37 -04:00
Jason Wen	94ed0608e6	models: use less strict chestnut detection state (#1948 )	2026-08-24 01:40:31 -04:00