Fix TURBOQUANT backend selection in cuda.py (#40060)

Signed-off-by: Michael Goin <mgoin64@gmail.com>

docs/design/attention_backends.md

@@ -106,6 +106,7 @@ Priority is **1 = highest** (tried first).
 | 2 | `FLASH_ATTN` |
 | 3 | `TRITON_ATTN` |
 | 4 | `FLEX_ATTENTION` |
+| 5 | `TURBOQUANT` |
 
 **Ampere/Hopper (SM 8.x-9.x):**
 
@@ -115,6 +116,7 @@ Priority is **1 = highest** (tried first).
 | 2 | `FLASHINFER` |
 | 3 | `TRITON_ATTN` |
 | 4 | `FLEX_ATTENTION` |
+| 5 | `TURBOQUANT` |
 
 ### MLA Attention (DeepSeek-style)
 

vllm/platforms/cuda.py

@@ -131,6 +131,7 @@ def _get_backend_priorities(
                 AttentionBackendEnum.FLASH_ATTN,
                 AttentionBackendEnum.TRITON_ATTN,
                 AttentionBackendEnum.FLEX_ATTENTION,
+                AttentionBackendEnum.TURBOQUANT,
             ]
         else:
             return [
@@ -138,6 +139,7 @@ def _get_backend_priorities(
                 AttentionBackendEnum.FLASHINFER,
                 AttentionBackendEnum.TRITON_ATTN,
                 AttentionBackendEnum.FLEX_ATTENTION,
+                AttentionBackendEnum.TURBOQUANT,
             ]
 
 
@@ -255,11 +257,6 @@ class CudaPlatformBase(Platform):
         valid_backends_priorities = []
         invalid_reasons: dict[AttentionBackendEnum, tuple[int, list[str]]] = {}
 
-        # TurboQuant KV cache: route directly to TQ backend
-        kv_cache_dtype = attn_selector_config.kv_cache_dtype
-        if kv_cache_dtype is not None and kv_cache_dtype.startswith("turboquant_"):
-            return [(AttentionBackendEnum.TURBOQUANT, 0)], {}
-
         backend_priorities = _get_backend_priorities(
             attn_selector_config.use_mla,
             device_capability,