diff --git a/vllm/models/deepseek_v4/nvidia/flashinfer_sparse.py b/vllm/models/deepseek_v4/nvidia/flashinfer_sparse.py
index 1848c1930d..19810f4667 100644
--- a/vllm/models/deepseek_v4/nvidia/flashinfer_sparse.py
+++ b/vllm/models/deepseek_v4/nvidia/flashinfer_sparse.py
@@ -60,6 +60,20 @@ def _packed_block_span(pool: torch.Tensor) -> int:
     return block_stride // token_stride
 
 
+# Sparse MLA h_q counts accepted natively (flashinfer>=0.6.14, #3545).
+_SPARSE_MLA_SUPPORTED_Q_HEADS = (8, 16, 32, 64, 128)
+
+
+def _pad_to_supported_q_heads(num_heads: int) -> int:
+    for supported in _SPARSE_MLA_SUPPORTED_Q_HEADS:
+        if num_heads <= supported:
+            return supported
+    raise ValueError(
+        f"DeepseekV4 FlashInfer MLA Sparse does not support {num_heads} heads "
+        "(sparse MLA kernel requires h_q in {8, 16, 32, 64, 128})."
+    )
+
+
 class DeepseekV4FlashInferMLASparseBackend(DeepseekV4FlashMLABackend):
     """FlashInfer backend using the DSv4 sparse metadata/cache layout.
 
@@ -164,13 +178,7 @@ class DeepseekV4FlashInferMLAAttention(DeepseekV4Attention):
 
     @classmethod
     def get_padded_num_q_heads(cls, num_heads: int) -> int:
-        # FP8 decode kernel only supports h_q = 64 or 128.
-        if num_heads > 128:
-            raise ValueError(
-                f"DeepseekV4 FlashInfer MLA Sparse does not support {num_heads} heads "
-                "(FP8 decode kernel requires h_q in {64, 128})."
-            )
-        return 64 if num_heads <= 64 else 128
+        return _pad_to_supported_q_heads(num_heads)
 
     def _o_proj(self, o: torch.Tensor, positions: torch.Tensor) -> torch.Tensor:
         return deep_gemm_fp8_o_proj(
@@ -545,18 +553,7 @@ class DeepseekV4FlashInferSM120Attention(DeepseekV4Attention):
 
     @classmethod
     def get_padded_num_q_heads(cls, num_heads: int) -> int:
-        if num_heads <= 16:
-            return 16
-        if num_heads <= 32:
-            return 32
-        if num_heads <= 64:
-            return 64
-        if num_heads <= 128:
-            return 128
-        raise ValueError(
-            f"DeepseekV4 FlashInfer MLA Sparse does not support {num_heads} heads "
-            "(SM120 kernel requires h_q in {16, 32, 64, 128})."
-        )
+        return _pad_to_supported_q_heads(num_heads)
 
     def _o_proj(self, o: torch.Tensor, positions: torch.Tensor) -> torch.Tensor:
         return deep_gemm_fp8_o_proj(