diff --git a/docs/design/moe_kernel_features.md b/docs/design/moe_kernel_features.md
index 6c02dcb76bec2..11c6e488f958f 100644
--- a/docs/design/moe_kernel_features.md
+++ b/docs/design/moe_kernel_features.md
@@ -92,7 +92,6 @@ To be used with a particular `FusedMoEPrepareAndFinalize` subclass, MoE kernels
 | gpt oss triton | standard | N/A | N/A | <sup>5</sup> | Y | Y | [`triton_kernel_fused_experts`][vllm.model_executor.layers.fused_moe.gpt_oss_triton_kernels_moe.triton_kernel_fused_experts],</br>[`OAITritonExperts`][vllm.model_executor.layers.fused_moe.gpt_oss_triton_kernels_moe.OAITritonExperts] |
 | marlin | standard,</br>batched | <sup>3</sup> / N/A | <sup>3</sup> / N/A | silu,</br>swigluoai | Y | Y | [`fused_marlin_moe`][vllm.model_executor.layers.fused_moe.fused_marlin_moe.fused_marlin_moe],</br>[`MarlinExperts`][vllm.model_executor.layers.fused_moe.fused_marlin_moe.MarlinExperts],</br>[`BatchedMarlinExperts`][vllm.model_executor.layers.fused_moe.fused_marlin_moe.BatchedMarlinExperts] |
 | trtllm | standard | mxfp4,</br>nvfp4 | G(16),G(32) | <sup>5</sup> | N | Y | [`TrtLlmGenExperts`][vllm.model_executor.layers.fused_moe.trtllm_moe.TrtLlmGenExperts] |
-| pallas | standard | N/A | N/A | silu | N | N | [`fused_moe`][vllm.model_executor.layers.fused_moe.moe_pallas.fused_moe] |
 | iterative | standard | N/A | N/A | silu | N | N | [`fused_moe`][vllm.model_executor.layers.fused_moe.moe_torch_iterative.fused_moe] |
 | rocm aiter moe | standard | fp8 | G(128),A,T | silu, gelu | Y | N | [`rocm_aiter_fused_experts`][vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe.rocm_aiter_fused_experts] |
 | cpu_fused_moe | standard | N/A | N/A | silu | N | N | [`CPUFusedMOE`][vllm.model_executor.layers.fused_moe.cpu_fused_moe.CPUFusedMOE] |
diff --git a/vllm/attention/layers/mm_encoder_attention.py b/vllm/attention/layers/mm_encoder_attention.py
index 1c1623b13f55a..138fc99114127 100644
--- a/vllm/attention/layers/mm_encoder_attention.py
+++ b/vllm/attention/layers/mm_encoder_attention.py
@@ -227,28 +227,3 @@ class MMEncoderAttention(CustomOp):
             "XPU only supports FLASH_ATTN for vision attention."
         )
         return self._forward_fa(query, key, value, cu_seqlens, max_seqlen)
-
-    def forward_tpu(
-        self,
-        query: torch.Tensor,
-        key: torch.Tensor,
-        value: torch.Tensor,
-        cu_seqlens: torch.Tensor | None = None,
-        max_seqlen: torch.Tensor | None = None,  # Only used for Flash Attention
-    ) -> torch.Tensor:
-        assert self.attn_backend == AttentionBackendEnum.PALLAS, (
-            f"MMEncoderAttention on TPU only supports PALLAS backend, "
-            f"but got {self.attn_backend}."
-        )
-        if cu_seqlens is None:
-            query, key, value = (x.transpose(1, 2) for x in (query, key, value))
-            from torch_xla.experimental.custom_kernel import flash_attention
-
-            out = flash_attention(query, key, value, sm_scale=self.scale)
-            out = out.transpose(1, 2)
-            return out
-        logger.warning_once(
-            "PALLAS backend with cu_seqlens is not supported for ViT yet. ",
-            "Falling back to SDPA implementation.",
-        )
-        return self._forward_sdpa(query, key, value, cu_seqlens)