diff --git a/config/training/dqn-production.toml b/config/training/dqn-production.toml
index 36ccf4d75..23ea42ce9 100644
--- a/config/training/dqn-production.toml
+++ b/config/training/dqn-production.toml
@@ -8,7 +8,7 @@
 
 [training]
 epochs = 200
-batch_size = 128
+batch_size = 0  # 0 = auto from VRAM via AutoBatchSizer
 learning_rate = 0.0001
 gamma = 0.99
 weight_decay = 0.0001
diff --git a/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs b/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
index 1ad7222a5..346e0312a 100644
--- a/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
+++ b/crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
@@ -2866,9 +2866,17 @@ impl GpuDqnTrainer {
         // Adam is deferred to replay_adam_and_readback() so the caller can
         // inject IQN/attention/ensemble gradients into grad_buf first.
         self.adam_step += 1;
-        self.stream
-            .memcpy_htod(&[self.adam_step], &mut self.t_buf)
-            .map_err(|e| MLError::ModelError(format!("HtoD adam_step: {e}")))?;
+        // Async HtoD for adam_step counter — no pipeline drain.
+        // t_buf address is captured by the graph; updating its value before
+        // replay is correct (graph captures addresses, not values).
+        unsafe {
+            cudarc::driver::sys::cuMemcpyHtoDAsync_v2(
+                self.t_buf.raw_ptr(),
+                (&self.adam_step as *const i32).cast(),
+                std::mem::size_of::<i32>(),
+                self.stream.cu_stream(),
+            );
+        }
         if self.graph_forward.is_none() {
             self.capture_training_graphs(online_dueling, online_branching)?;
         }
@@ -3039,9 +3047,14 @@ impl GpuDqnTrainer {
 
         // ── Update Adam step counter on device (OUTSIDE graph) ───────
         self.adam_step += 1;
-        self.stream
-            .memcpy_htod(&[self.adam_step], &mut self.t_buf)
-            .map_err(|e| MLError::ModelError(format!("HtoD adam_step: {e}")))?;
+        unsafe {
+            cudarc::driver::sys::cuMemcpyHtoDAsync_v2(
+                self.t_buf.raw_ptr(),
+                (&self.adam_step as *const i32).cast(),
+                std::mem::size_of::<i32>(),
+                self.stream.cu_stream(),
+            );
+        }
 
         // ── Execute training step (split graph: forward then adam) ──
         if self.graph_forward.is_none() {
@@ -3431,9 +3444,14 @@ impl GpuDqnTrainer {
     ) -> Result<FusedTrainScalars, MLError> {
         // ── Update Adam step counter on device (OUTSIDE graph) ───────
         self.adam_step += 1;
-        self.stream
-            .memcpy_htod(&[self.adam_step], &mut self.t_buf)
-            .map_err(|e| MLError::ModelError(format!("HtoD adam_step: {e}")))?;
+        unsafe {
+            cudarc::driver::sys::cuMemcpyHtoDAsync_v2(
+                self.t_buf.raw_ptr(),
+                (&self.adam_step as *const i32).cast(),
+                std::mem::size_of::<i32>(),
+                self.stream.cu_stream(),
+            );
+        }
 
         // ── Execute training step (split graph: forward then adam) ──
         if self.graph_forward.is_none() {