diff --git a/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs b/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
index d082d4494..5b4aae5be 100644
--- a/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
+++ b/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
@@ -3159,11 +3159,10 @@ impl GpuDqnTrainer {
                 self.stream.cu_stream(),
             );
         }
-        if self.graph_forward.is_none() {
-            self.capture_training_graphs(online_dueling, online_branching)?;
-        }
+        // DIAG: skip ALL graph capture — run forward+backward ungraphed every step.
+        // If this fixes H100 collapse, the graph recapture path is the root cause.
         self.update_stochastic_depth_mask()?;
-        self.replay_forward()?;
+        self.submit_forward_ops_main()?;
         Ok(FusedTrainScalars { total_loss: 0.0, grad_norm: 0.0 })
     }
 
@@ -3813,6 +3812,7 @@ impl GpuDqnTrainer {
     /// Replay graph_adam only (grad_norm → Adam → unflatten).
     /// Must be called AFTER replay_forward() and any auxiliary gradient injection.
     pub fn replay_adam(&self) -> Result<(), MLError> {
+        // Keep graph_adam replay — it's captured once and never invalidated
         if let Some(ref graph) = self.graph_adam {
             graph.0.launch().map_err(|e| {
                 MLError::ModelError(format!("CUDA graph_adam replay: {e}"))