diff --git a/sunnypilot/modeld/modeld.py b/sunnypilot/modeld/modeld.py
index 91d9f84d60..7540b234c7 100755
--- a/sunnypilot/modeld/modeld.py
+++ b/sunnypilot/modeld/modeld.py
@@ -52,11 +52,9 @@ class ModelState:
     self.full_features_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32)
     self.desire_20Hz =  np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.DESIRE_LEN), dtype=np.float32)
 
-    # img buffers are managed in openCL transform code
-    self.inputs = prepare_inputs()
-
     model_paths = load_model()
     model_metadata = load_metadata()
+    self.inputs = prepare_inputs(model_metadata)
 
     self.output_slices = model_metadata['output_slices']
     net_output_size = model_metadata['output_shapes']['outputs'][1]
@@ -239,7 +237,10 @@ def main(demo=False):
     if prepare_only:
       cloudlog.error(f"skipping model eval. Dropped {vipc_dropped_frames} frames")
 
-    inputs = parse_runner_inputs(vec_desire, traffic_convention)
+    inputs: dict[str, np.ndarray] = {
+      'desire': vec_desire,
+      'traffic_convention': traffic_convention,
+    }
 
     mt1 = time.perf_counter()
     model_output = model.run(buf_main, buf_extra, model_transform_main, model_transform_extra, inputs, prepare_only)
diff --git a/sunnypilot/modeld/runners/run_helpers.py b/sunnypilot/modeld/runners/run_helpers.py
index 37503c8bfc..1639660062 100644
--- a/sunnypilot/modeld/runners/run_helpers.py
+++ b/sunnypilot/modeld/runners/run_helpers.py
@@ -13,30 +13,30 @@ from openpilot.sunnypilot.models.helpers import get_active_bundle
 from openpilot.system.hardware import PC
 from openpilot.system.hardware.hw import Paths
 
-USE_ONNX = int(os.getenv('USE_ONNX', str(int(PC))))
+USE_ONNX = os.getenv('USE_ONNX', PC)
 
 CUSTOM_MODEL_PATH = Paths.model_root()
-METADATA_PATH = Path(__file__).parent / 'models/supercombo_metadata.pkl'
+METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'
 
 ModelManager = custom.ModelManagerSP
 
 
 def load_model():
   if USE_ONNX:
-    model_paths = {ModelRunner.ONNX: Path(__file__).parent / 'models/supercombo.onnx'}
+    model_paths = {ModelRunner.ONNX: Path(__file__).parent / '../models/supercombo.onnx'}
   elif bundle := get_active_bundle():
     drive_model = next(model for model in bundle.models if model.type == ModelManager.Type.drive)
     model_paths = {ModelRunner.THNEED: f"{CUSTOM_MODEL_PATH}/{drive_model.fileName}"}
   else:
-    model_paths = {ModelRunner.THNEED: Path(__file__).parent / 'models/supercombo.thneed'}
+    model_paths = {ModelRunner.THNEED: Path(__file__).parent / '../models/supercombo.thneed'}
 
   return model_paths
 
 
 def load_metadata():
   if bundle := get_active_bundle():
-    drive_model = next(model for model in bundle.models if model.type == ModelManager.Type.metadata)
-    metadata_path = f"{CUSTOM_MODEL_PATH}/{drive_model.fileName}"
+    metadata_model = next(model for model in bundle.models if model.type == ModelManager.Type.metadata)
+    metadata_path = f"{CUSTOM_MODEL_PATH}/{metadata_model.fileName}"
   else:
     metadata_path = METADATA_PATH
 
@@ -46,22 +46,12 @@ def load_metadata():
   return metadata
 
 
-def prepare_inputs() -> dict[str, np.ndarray]:
-  model_metadata = load_metadata()
-
+def prepare_inputs(metadata) -> dict[str, np.ndarray]:
+  # img buffers are managed in openCL transform code
   inputs: dict[str, np.ndarray] = {
     key: np.zeros(shape, dtype=np.float32)
-    for key, shape in model_metadata['input_shapes'].items()
+    for key, shape in metadata['input_shapes'].items()
     if key not in ['input_imgs', 'big_input_imgs']
   }
 
   return inputs
-
-
-def parse_runner_inputs(vec_desire, traffic_convention) -> dict[str, np.ndarray]:
-  inputs: dict[str, np.ndarray] = {
-    'desire': vec_desire,
-    'traffic_convention': traffic_convention,
-  }
-
-  return inputs