diff --git a/vllm/attention/backends/mla/common.py b/vllm/attention/backends/mla/common.py
index 4dd562be3838..225fee8d2a0d 100644
--- a/vllm/attention/backends/mla/common.py
+++ b/vllm/attention/backends/mla/common.py
@@ -232,6 +232,7 @@ from vllm.model_executor.layers.quantization.utils.quant_utils import (
 from vllm.model_executor.layers.rotary_embedding import (
     DeepseekScalingRotaryEmbedding, RotaryEmbedding)
 from vllm.multimodal import MultiModalPlaceholderMap
+from vllm.platforms import current_platform
 from vllm.utils import async_tensor_h2d, cdiv, make_tensor_with_pad, round_down
 
 try:
@@ -1371,18 +1372,35 @@ class MLACommonImpl(MLAAttentionImpl[T], Generic[T]):
         v_padded = torch.nn.functional.pad(v, [0, q.shape[-1] - v.shape[-1]],
                                            value=0)
 
-        output = self.flash_attn_varlen_func(
-            q=q,
-            k=k,
-            v=v_padded,
-            cu_seqlens_q=prefill_metadata.query_start_loc,
-            cu_seqlens_k=prefill_metadata.query_start_loc,
-            max_seqlen_q=prefill_metadata.max_prefill_seq_len,
-            max_seqlen_k=prefill_metadata.max_prefill_seq_len,
-            softmax_scale=self.scale,
-            causal=True,
-            return_softmax_lse=has_context,
-        )
+        if has_context:
+            if not current_platform.is_cuda():
+                raise NotImplementedError(
+                    "Chunked Prefill for MLA is not currently supported on"
+                    "non-cuda platforms")
+            output = self.flash_attn_varlen_func(
+                q=q,
+                k=k,
+                v=v_padded,
+                cu_seqlens_q=prefill_metadata.query_start_loc,
+                cu_seqlens_k=prefill_metadata.query_start_loc,
+                max_seqlen_q=prefill_metadata.max_prefill_seq_len,
+                max_seqlen_k=prefill_metadata.max_prefill_seq_len,
+                softmax_scale=self.scale,
+                causal=True,
+                return_softmax_lse=True,
+            )
+        else:
+            output = self.flash_attn_varlen_func(
+                q=q,
+                k=k,
+                v=v_padded,
+                cu_seqlens_q=prefill_metadata.query_start_loc,
+                cu_seqlens_k=prefill_metadata.query_start_loc,
+                max_seqlen_q=prefill_metadata.max_prefill_seq_len,
+                max_seqlen_k=prefill_metadata.max_prefill_seq_len,
+                softmax_scale=self.scale,
+                causal=True,
+            )
 
         if has_context:
             suffix_output, suffix_lse = output
diff --git a/vllm/config.py b/vllm/config.py
index 8e1ce87438af..a5d8ee9303d0 100644
--- a/vllm/config.py
+++ b/vllm/config.py
@@ -3422,6 +3422,20 @@ class VllmConfig:
                            "Disabling `torch.compile`.")
             self.compilation_config.level = CompilationLevel.NO_COMPILATION
 
+        if self.model_config and self.model_config.use_mla and \
+            not current_platform.is_cuda():
+            logger.info(
+                "MLA is enabled on a non-cuda platform; forcing chunked "
+                "prefill and prefix caching to be disabled.")
+            self.scheduler_config.enable_chunked_prefill = False
+            self.scheduler_config.chunked_prefill_enabled = False
+            self.scheduler_config.max_num_batched_tokens = max(
+                self.scheduler_config.max_model_len,
+                _DEFAULT_MAX_NUM_BATCHED_TOKENS)
+
+            if self.cache_config is not None:
+                self.cache_config.enable_prefix_caching = False
+
         current_platform.check_and_update_config(self)
 
         if not self.instance_id: