diff --git a/README.md b/README.md
index 3f03fd7f1..efb69c043 100644
--- a/README.md
+++ b/README.md
@@ -135,7 +135,7 @@ sky status --endpoint 30000 sglang
 
 
 ### Common Notes
-- [FlashInfer](https://github.com/flashinfer-ai/flashinfer) is currently one of the dependencies that must be installed for SGLang. If you are using NVIDIA GPU devices below sm80, such as T4, you can't use SGLang for the time being. We expect to resolve this issue soon, so please stay tuned. If you encounter any FlashInfer-related issues on sm80+ devices (e.g., A100, L40S, H100), consider using Triton's kernel by `--disable-flashinfer --disable-flashinfer-sampling` and raise a issue.
+- [FlashInfer](https://github.com/flashinfer-ai/flashinfer) is currently one of the dependencies that must be installed for SGLang. It only supports sm75 and above. If you encounter any FlashInfer-related issues on sm75+ devices (e.g., T4, A10, A100, L4, L40S, H100), consider using Triton's kernel by `--disable-flashinfer --disable-flashinfer-sampling` and raise an issue.
 - If you only need to use the OpenAI backend, you can avoid installing other dependencies by using `pip install "sglang[openai]"`.
 
 ## Backend: SGLang Runtime (SRT)
diff --git a/python/sglang/srt/layers/activation.py b/python/sglang/srt/layers/activation.py
index 832d2b701..5df387cb2 100644
--- a/python/sglang/srt/layers/activation.py
+++ b/python/sglang/srt/layers/activation.py
@@ -30,18 +30,11 @@ from vllm.model_executor.utils import set_weight_attrs
 
 
 class SiluAndMul(CustomOp):
-    def __init__(self, **kwargs):
-        super().__init__()
-        self.is_lower_sm80 = torch.cuda.get_device_capability()[0] < 8
-
     def forward_native(self, x: torch.Tensor) -> torch.Tensor:
         d = x.shape[-1] // 2
         return F.silu(x[..., :d]) * x[..., d:]
 
     def forward_cuda(self, x: torch.Tensor) -> torch.Tensor:
-        if self.is_lower_sm80:
-            return self.forward_native(x)
-
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
         out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
diff --git a/python/sglang/srt/layers/layernorm.py b/python/sglang/srt/layers/layernorm.py
index 6cea85404..ac4d368d3 100644
--- a/python/sglang/srt/layers/layernorm.py
+++ b/python/sglang/srt/layers/layernorm.py
@@ -32,15 +32,12 @@ class RMSNorm(CustomOp):
         super().__init__()
         self.weight = nn.Parameter(torch.ones(hidden_size))
         self.variance_epsilon = eps
-        self.is_lower_sm80 = torch.cuda.get_device_capability()[0] < 8
 
     def forward_cuda(
         self,
         x: torch.Tensor,
         residual: Optional[torch.Tensor] = None,
     ) -> Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]]:
-        if self.is_lower_sm80:
-            return self.forward_native(x, residual)
 
         if residual is not None:
             fused_add_rmsnorm(x, residual, self.weight.data, self.variance_epsilon)
diff --git a/python/sglang/srt/model_executor/model_runner.py b/python/sglang/srt/model_executor/model_runner.py
index 006606114..0dd9f8c20 100644
--- a/python/sglang/srt/model_executor/model_runner.py
+++ b/python/sglang/srt/model_executor/model_runner.py
@@ -161,6 +161,8 @@ class ModelRunner:
                 "Compute capability below sm80. Use float16 due to lack of bfloat16 support."
             )
             self.server_args.dtype = "float16"
+            if torch.cuda.get_device_capability()[1] < 5:
+                raise RuntimeError("SGLang only supports sm75 and above.")
 
         monkey_patch_vllm_dummy_weight_loader()
         self.device_config = DeviceConfig()
diff --git a/python/sglang/srt/server.py b/python/sglang/srt/server.py
index 6d1fc9fda..f3d1ab0f9 100644
--- a/python/sglang/srt/server.py
+++ b/python/sglang/srt/server.py
@@ -421,7 +421,7 @@ def _set_envs_and_config(server_args: ServerArgs):
     if not server_args.disable_flashinfer:
         assert_pkg_version(
             "flashinfer",
-            "0.1.5",
+            "0.1.6",
             "Please uninstall the old version and "
             "reinstall the latest version by following the instructions "
             "at https://docs.flashinfer.ai/installation.html.",