diff --git a/docs/design/moe_kernel_features.md b/docs/design/moe_kernel_features.md
index 53f91de55e..bdf4075102 100644
--- a/docs/design/moe_kernel_features.md
+++ b/docs/design/moe_kernel_features.md
@@ -32,7 +32,7 @@ th {
 
 | Backend | Output act. format | Quant. types | Quant. format | Async | Apply Weight On Input | Subclass |
 | ------- | ------------------ | ------------ | ------------- | ----- | --------------------- | --------- |
-| naive | standard | all<sup>1</sup> | G,A,T | N | <sup>6</sup> | [layer.py][vllm.model_executor.layers.fused_moe.runner.MoERunner] |
+| naive | standard | all<sup>1</sup> | G,A,T | N | <sup>6</sup> | [`MoERunner`][vllm.model_executor.layers.fused_moe.runner.moe_runner.MoERunner] |
 | deepep_high_throughput | standard | fp8 | G(128),A,T<sup>2</sup> | Y | Y | [`DeepEPHTPrepareAndFinalize`][vllm.model_executor.layers.fused_moe.prepare_finalize.deepep_ht.DeepEPHTPrepareAndFinalize] |
 | deepep_low_latency | batched | fp8 | G(128),A,T<sup>3</sup> | Y | Y | [`DeepEPLLPrepareAndFinalize`][vllm.model_executor.layers.fused_moe.prepare_finalize.deepep_ll.DeepEPLLPrepareAndFinalize] |
 | flashinfer_nvlink_two_sided | standard | nvfp4,fp8 | G,A,T | N | N | [`FlashInferNVLinkTwoSidedPrepareAndFinalize`][vllm.model_executor.layers.fused_moe.prepare_finalize.flashinfer_nvlink_two_sided.FlashInferNVLinkTwoSidedPrepareAndFinalize] |
diff --git a/vllm/model_executor/kernels/linear/mxfp6/base.py b/vllm/model_executor/kernels/linear/mxfp6/base.py
index b3ba208634..ef00bc5764 100644
--- a/vllm/model_executor/kernels/linear/mxfp6/base.py
+++ b/vllm/model_executor/kernels/linear/mxfp6/base.py
@@ -18,7 +18,7 @@ class MxFp6LinearLayerConfig:
 
     Attributes:
         weight_quant_key: Identifies the weight quantization format. Can be
-        kMxfp6E2M3Static or kMxfp6E3M2Static.
+            kMxfp6E2M3Static or kMxfp6E3M2Static.
         activation_quant_key: Identifies the activation quantization format,
             or `None` when activations must not be quantized.
     """