Revert "[Attention][MLA] Make `FLASHINFER_MLA` the default MLA backen… (#32484)

Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>

vllm/config/attention.py

@@ -35,7 +35,7 @@ class AttentionConfig:
     use_cudnn_prefill: bool = False
     """Whether to use cudnn prefill."""
 
-    use_trtllm_ragged_deepseek_prefill: bool = True
+    use_trtllm_ragged_deepseek_prefill: bool = False
     """Whether to use TRTLLM ragged deepseek prefill."""
 
     use_trtllm_attention: bool | None = None

vllm/model_executor/layers/attention/mla_attention.py

@@ -450,6 +450,7 @@ def use_flashinfer_prefill() -> bool:
         not vllm_config.attention_config.disable_flashinfer_prefill
         and flashinfer_available
         and not vllm_config.attention_config.use_cudnn_prefill
+        and not vllm_config.attention_config.use_trtllm_ragged_deepseek_prefill
         and current_platform.is_device_capability_family(100)
     )
 
@@ -1323,27 +1324,25 @@ class MLACommonImpl(MLACommonBaseImpl[M], Generic[M]):
     def __init__(self, *args, **kwargs) -> None:
         super().__init__(*args, **kwargs)
 
-        if use_trtllm_ragged_deepseek_prefill():
-            logger.info_once(
-                "Using TRT-LLM ragged DeepSeek prefill for MLA", scope="local"
-            )
+        if use_flashinfer_prefill():
+            logger.debug_once("Using FlashInfer prefill for MLA")
+            self._run_prefill_context_chunk = self._run_prefill_context_chunk_fi
+            self._run_prefill_new_tokens = self._run_prefill_new_tokens_fi
+            self._pad_v = False
+        elif use_trtllm_ragged_deepseek_prefill():
+            logger.debug_once("Using TRT-LLM ragged DeepSeek prefill for MLA")
             self._run_prefill_context_chunk = (
                 self._run_prefill_context_chunk_trtllm_ragged
             )
             self._run_prefill_new_tokens = self._run_prefill_new_tokens_trtllm_ragged
             self._pad_v = False
-        elif use_flashinfer_prefill():
-            logger.info_once("Using FlashInfer prefill for MLA")
-            self._run_prefill_context_chunk = self._run_prefill_context_chunk_fi
-            self._run_prefill_new_tokens = self._run_prefill_new_tokens_fi
-            self._pad_v = False
         elif use_cudnn_prefill():
-            logger.info_once("Using CUDNN prefill for MLA", scope="local")
+            logger.debug_once("Using CUDNN prefill for MLA")
             self._run_prefill_context_chunk = self._run_prefill_context_chunk_cudnn
             self._run_prefill_new_tokens = self._run_prefill_new_tokens_cudnn
             self._pad_v = False
         else:  # Use FlashAttention
-            logger.info_once("Using FlashAttention prefill for MLA", scope="local")
+            logger.debug_once("Using FlashAttention prefill for MLA")
             self._run_prefill_context_chunk = self._run_prefill_context_chunk_fa
             self._run_prefill_new_tokens = self._run_prefill_new_tokens_fa
 

vllm/platforms/cuda.py

@@ -50,8 +50,8 @@ def _get_backend_priorities(
     if use_mla:
         if device_capability.major == 10:
             return [
-                AttentionBackendEnum.FLASHINFER_MLA,
                 AttentionBackendEnum.CUTLASS_MLA,
+                AttentionBackendEnum.FLASHINFER_MLA,
                 AttentionBackendEnum.FLASH_ATTN_MLA,
                 AttentionBackendEnum.FLASHMLA,
                 AttentionBackendEnum.TRITON_MLA,
@@ -183,12 +183,12 @@ class CudaPlatformBase(Platform):
             if vllm_config.attention_config.backend is None:
                 # Default case
                 if cls.is_device_capability_family(100) and not use_sparse:
-                    # Blackwell => Force FlashInferMLA (unless sparse, i.e. DSv3.2).
-                    use_flashinfer_mla = True
+                    # Blackwell => Force CutlassMLA (unless sparse, i.e. DSv3.2).
+                    use_cutlass_mla = True
                     # Set the backend in AttentionConfig so it's used during
                     # backend selection
                     vllm_config.attention_config.backend = (
-                        AttentionBackendEnum.FLASHINFER_MLA
+                        AttentionBackendEnum.CUTLASS_MLA
                     )
                 else:
                     # Not Blackwell