diff --git a/tests/unittest/_torch/modeling/test_modeling_qwen3_5_vl.py b/tests/unittest/_torch/modeling/test_modeling_qwen3_5_vl.py
index fe097dabd79a..5c13c3a73853 100644
--- a/tests/unittest/_torch/modeling/test_modeling_qwen3_5_vl.py
+++ b/tests/unittest/_torch/modeling/test_modeling_qwen3_5_vl.py
@@ -143,15 +143,24 @@ def test_qwen35_dense_vl_resolves_mamba_ssm_cache_dtype(
     config = load_pretrained_config(str(_write_qwen35_dense_vl_config(tmp_path)))
     model_config = ModelConfig(pretrained_config=config)
 
+    # "auto" keeps the SSM cache in the model weights dtype for performance:
+    # the checkpoint's mamba_ssm_dtype=float32 expresses SSM compute intent,
+    # and honoring it for cache allocation disables the FlashInfer bf16-state
+    # GDN decode kernel and doubles state memory traffic.
     validate_and_set_mamba_ssm_cache_dtype(model_config, "auto")
-    assert model_config.quant_config.mamba_ssm_cache_dtype is torch.float32
+    assert model_config.quant_config.mamba_ssm_cache_dtype is torch.bfloat16
 
     mamba_params = extract_mamba_kv_cache_params(
         config.text_config,
         quant_config=model_config.quant_config,
     )
     assert mamba_params.dtype is torch.bfloat16
-    assert mamba_params.mamba_ssm_cache_dtype is torch.float32
+    assert mamba_params.mamba_ssm_cache_dtype is torch.bfloat16
+
+    # Explicit opt-in honors the checkpoint's fp32 SSM state intent.
+    opt_in_config = ModelConfig(pretrained_config=config)
+    validate_and_set_mamba_ssm_cache_dtype(opt_in_config, "float32")
+    assert opt_in_config.quant_config.mamba_ssm_cache_dtype is torch.float32
 
 
 def test_qwen35_dense_vl_resolves_model_and_mapper(tmp_path: Path) -> None: