diff --git a/tests/compile/passes/test_fusion_attn.py b/tests/compile/passes/test_fusion_attn.py
index 5c2d03213..94014ca01 100644
--- a/tests/compile/passes/test_fusion_attn.py
+++ b/tests/compile/passes/test_fusion_attn.py
@@ -53,6 +53,7 @@ class AttentionQuantPatternModel(torch.nn.Module):
         kv_cache_dtype: torch.dtype,
         device: torch.device,
         vllm_config: VllmConfig,
+        block_size: int,
         **kwargs,
     ):
         super().__init__()
@@ -74,7 +75,7 @@ class AttentionQuantPatternModel(torch.nn.Module):
         self.attn._k_scale = self.attn._k_scale.to(device)
         self.attn._v_scale = self.attn._v_scale.to(device)
 
-        self.block_size = 16
+        self.block_size = block_size
 
         # Initialize attn MetadataBuilder
         self.builder = self.attn.attn_backend.get_builder_cls()(
@@ -299,6 +300,9 @@ def test_attention_quant_pattern(
     torch.set_default_dtype(dtype)
     torch.manual_seed(42)
 
+    backend_cls = backend.get_class()
+    block_size = backend_cls.get_preferred_block_size(16)
+
     model_config = ModelConfig(
         model=model_name,
         max_model_len=2048,
@@ -342,6 +346,7 @@ def test_attention_quant_pattern(
             kv_cache_dtype=FP8_DTYPE,
             device=device,
             vllm_config=vllm_config_unfused,
+            block_size=block_size,
         )
         model_unfused = model_unfused.to(device)
         result_unfused_0 = model_unfused(q, k, v)  # noqa: F841  HACK: See #131044
@@ -370,6 +375,7 @@ def test_attention_quant_pattern(
             device=device,
             vllm_config=vllm_config,
             w=model_unfused.w,
+            block_size=block_size,
         )
         model_fused = model_fused.to(device)