diff --git a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
index a7ae314c8..b54420ffb 100644
--- a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
+++ b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
@@ -5,7 +5,6 @@ import numpy as np
 from cereal import log
 from openpilot.common.numpy_fast import clip, interp
 from openpilot.common.realtime import DT_MDL
-from openpilot.common.swaglog import cloudlog
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.conversions import Conversions as CV
 # WARNING: imports outside of constants will not trigger a rebuild
@@ -422,9 +421,6 @@ class LongitudinalMpc:
       scale = float(np.interp(uncertainty, [0.45, 0.60], [1.2, 1.5]))
       speed_jerk *= scale
 
-    if abs(filter_time_factor - prev_filter_time_factor) > 1e-3:
-      cloudlog.error(f"LON_FILTER; filter_time_factor={filter_time_factor:.2f}; uncertainty={uncertainty:.3f}; v_ego={v_ego:.2f} mps; lead_dist={lead_dist:.2f} m; accel_reengage={accel_reengage}")
-
     if self.mode == 'acc':
       a_change_cost = acceleration_jerk if prev_accel_constraint else 0
       cost_weights = [self.current_x_ego_cost, X_EGO_COST, V_EGO_COST, A_EGO_COST, a_change_cost, speed_jerk]
@@ -627,11 +623,7 @@ class LongitudinalMpc:
 
     self.prev_a = np.interp(T_IDXS + self.dt, T_IDXS, self.a_solution)
 
-    t = time.monotonic()
     if self.solution_status != 0:
-      if t > self.last_cloudlog_t + 5.0:
-        self.last_cloudlog_t = t
-        cloudlog.warning(f"Long mpc reset, solution_status: {self.solution_status}")
       self.reset()
       # reset = 1
     # print(f"long_mpc timings: total internal {self.solve_time:.2e}, external: {(time.monotonic() - t0):.2e} qp {self.time_qp_solution:.2e}, \
diff --git a/selfdrive/controls/lib/longitudinal_planner.py b/selfdrive/controls/lib/longitudinal_planner.py
index c9fc80407..7c0eb0a1e 100644
--- a/selfdrive/controls/lib/longitudinal_planner.py
+++ b/selfdrive/controls/lib/longitudinal_planner.py
@@ -111,9 +111,6 @@ class LongitudinalPlanner:
     self.a_desired_trajectory = np.zeros(CONTROL_N)
     self.j_desired_trajectory = np.zeros(CONTROL_N)
     self.solverExecutionTime = 0.0
-    # logging cadence & state
-    self.last_uncert_log_t = 0.0
-    self.prev_uncert_over = False
 
     # ---- Rubberband mitigation state ----
     # Two uncertainty tracks (slow/fast) for asymmetric gating
@@ -344,19 +341,6 @@ class LongitudinalPlanner:
 
     # now_t defined earlier
     over = uncertainty > 1.0
-    # Log on threshold edge or at ~1 Hz
-    if over != self.prev_uncert_over or (now_t - self.last_uncert_log_t) > 1.0:
-      try:
-        cloudlog.error(
-          f"LON_UNCERT; v_ego={v_ego:.2f} mps; desireEntropy={desire_entropy:.3f}; "
-          f"brakeRawMax={(raw_brake_max if 'raw_brake_max' in locals() else -1.0):.3f}; "
-          f"brakeDecayed={(disengage_risk if 'disengage_risk' in locals() else -1.0):.3f}; "
-          f"lam={(lam if 'lam' in locals() else -1.0):.2f}; uncertainty={uncertainty:.3f}; over={over}"
-        )
-      except Exception as e:
-        cloudlog.warning(f"LON_UNCERT log error: {e}")
-      self.prev_uncert_over = over
-      self.last_uncert_log_t = now_t
 
     # Asymmetric accel release with hysteresis + dwell to prevent on/off pulsing
     rise_dwell_s, fall_dwell_s = 0.6, 0.4