diff --git a/docs/start/install.md b/docs/start/install.md
index 2d778bf72..88a920363 100644
--- a/docs/start/install.md
+++ b/docs/start/install.md
@@ -22,7 +22,7 @@ pip install sgl-kernel --force-reinstall --no-deps
 pip install -e "python[all]" --find-links https://flashinfer.ai/whl/cu124/torch2.5/flashinfer/
 ```
 
-Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions. If you meet with issue like **ImportError: cannot import name `_grouped_size_compiled_for_decode_kernels`**, installing FlashInfer with some older version like 0.1.6 instead of the latest version could solve it.
+Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions.
 
 Note: To AMD ROCm system with Instinct/MI GPUs, do following instead:
 
diff --git a/python/sglang/srt/layers/attention/flashinfer_backend.py b/python/sglang/srt/layers/attention/flashinfer_backend.py
index 75ed9b3fc..e899bcb7e 100644
--- a/python/sglang/srt/layers/attention/flashinfer_backend.py
+++ b/python/sglang/srt/layers/attention/flashinfer_backend.py
@@ -1077,21 +1077,6 @@ def should_use_tensor_core(
     if env_override is not None:
         return env_override.lower() == "true"
 
-    # Try to use _grouped_size_compiled_for_decode_kernels if available
-    # This is for flashinfer <=0.1.6. Otherwise, there is an accuracy bug
-    try:
-        from flashinfer.decode import _grouped_size_compiled_for_decode_kernels
-
-        if not _grouped_size_compiled_for_decode_kernels(
-            num_attention_heads,
-            num_kv_heads,
-        ):
-            return True
-        else:
-            return False
-    except (ImportError, AttributeError):
-        pass
-
     # Calculate GQA group size
     gqa_group_size = num_attention_heads // num_kv_heads