diff --git a/selfdrive/modeld/models/driving_policy.onnx b/selfdrive/modeld/models/driving_policy.onnx
index ee9a9b6ec1..9bb9254a0f 100644
--- a/selfdrive/modeld/models/driving_policy.onnx
+++ b/selfdrive/modeld/models/driving_policy.onnx
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ef059460a95076f9a8600abb8c9d56c8c3b7384505b158064e2e875458b965bb
-size 15701037
+oid sha256:02cf21ce7e9784c6009cc32a6f1ea22482911897b6d944419477973284052716
+size 15583374
diff --git a/selfdrive/modeld/models/driving_vision.onnx b/selfdrive/modeld/models/driving_vision.onnx
index 6cdca2f93c..18f63358db 100644
--- a/selfdrive/modeld/models/driving_vision.onnx
+++ b/selfdrive/modeld/models/driving_vision.onnx
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:afee02876ed51f21883e731990a252fd57afda6a78700c41fbf22d8cb288b4b5
-size 46147818
+oid sha256:c824f68646a3b94f117f01c70dc8316fb466e05fbd42ccdba440b8a8dc86914b
+size 46265993
diff --git a/selfdrive/modeld/parse_model_outputs.py b/selfdrive/modeld/parse_model_outputs.py
index d5a5dc1bb4..b89de27594 100644
--- a/selfdrive/modeld/parse_model_outputs.py
+++ b/selfdrive/modeld/parse_model_outputs.py
@@ -93,6 +93,9 @@ class Parser:
     self.parse_binary_crossentropy('lane_lines_prob', outs)
     self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH))
     self.parse_binary_crossentropy('meta', outs)
+    self.parse_binary_crossentropy('lead_prob', outs)
+    self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
+      out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
     return outs
 
   def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
@@ -103,9 +106,6 @@ class Parser:
     if 'desired_curvature' in outs:
       self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(ModelConstants.DESIRED_CURV_WIDTH,))
     self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
-    self.parse_binary_crossentropy('lead_prob', outs)
-    self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
-      out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
     return outs
 
   def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: