diff --git a/tests/unit/test_cuda_graph_stream.py b/tests/unit/test_cuda_graph_stream.py
new file mode 100644
index 00000000..c0527b97
--- /dev/null
+++ b/tests/unit/test_cuda_graph_stream.py
@@ -0,0 +1,78 @@
+"""Minimal CUDA graph test with explicit stream management."""
+import torch
+
+def test_explicit_stream():
+    """Test CUDA graph with explicit per-device streams."""
+    results = {}
+    for gpu in range(8):
+        device = f'cuda:{gpu}'
+        
+        # Create a dedicated stream for this device
+        s = torch.cuda.Stream(device=device)
+        
+        # Create tensors on the correct device
+        x = torch.ones(1, 4, 7168, dtype=torch.bfloat16, device=device)
+        y = torch.zeros(1, 4, 7168, dtype=torch.bfloat16, device=device)
+        
+        # Capture on the explicit stream
+        g = torch.cuda.CUDAGraph()
+        with torch.cuda.graph(g, stream=s):
+            y.copy_(x * 2.0)
+        
+        # Update input
+        x.fill_(3.0)
+        
+        # Replay on the SAME stream
+        with torch.cuda.stream(s):
+            g.replay()
+        
+        torch.cuda.synchronize()
+        y_max = y.abs().max().item()
+        expected = 6.0
+        status = "OK" if abs(y_max - expected) < 0.1 else f"WRONG (expected {expected}, got {y_max})"
+        results[gpu] = y_max
+        print(f"  GPU {gpu}: y_max={y_max:.2f} — {status}")
+    
+    return results
+
+def test_set_device_before_each_op():
+    """Test with explicit set_device before each operation."""
+    results = {}
+    for gpu in range(8):
+        torch.cuda.set_device(gpu)
+        device = f'cuda:{gpu}'
+        
+        x = torch.ones(1, 4, 7168, dtype=torch.bfloat16, device=device)
+        y = torch.zeros(1, 4, 7168, dtype=torch.bfloat16, device=device)
+        
+        # Use default stream on the current device
+        g = torch.cuda.CUDAGraph()
+        with torch.cuda.graph(g):
+            # Explicitly set device INSIDE the graph capture
+            torch.cuda.set_device(gpu)
+            y.copy_(x * 2.0)
+        
+        # Update input
+        x.fill_(3.0)
+        
+        # Replay
+        torch.cuda.set_device(gpu)
+        g.replay()
+        torch.cuda.synchronize()
+        
+        y_max = y.abs().max().item()
+        expected = 6.0
+        status = "OK" if abs(y_max - expected) < 0.1 else f"WRONG (expected {expected}, got {y_max})"
+        results[gpu] = y_max
+        print(f"  GPU {gpu}: y_max={y_max:.2f} — {status}")
+    
+    return results
+
+if __name__ == "__main__":
+    print("=== Test with explicit stream ===")
+    test_explicit_stream()
+    
+    print("\n=== Test with set_device inside capture ===")
+    test_set_device_before_each_op()
+    
+    print("\nDone.")