diff --git a/vllm/model_executor/layers/mamba/mamba_mixer2.py b/vllm/model_executor/layers/mamba/mamba_mixer2.py
index a4efec7948e5..e39ceabd3988 100644
--- a/vllm/model_executor/layers/mamba/mamba_mixer2.py
+++ b/vllm/model_executor/layers/mamba/mamba_mixer2.py
@@ -679,14 +679,18 @@ def conv_ssm_forward(
             # for prefill and decode
             block_idx_last_computed_token_d, block_idx_last_computed_token_p = (
                 torch.split(
-                    attn_metadata.block_idx_last_computed_token,
+                    attn_metadata.block_idx_last_computed_token[
+                        : num_decodes + num_prefills
+                    ],
                     [num_decodes, num_prefills],
                     dim=0,
                 )
             )
             block_idx_last_scheduled_token_d, block_idx_last_scheduled_token_p = (
                 torch.split(
-                    attn_metadata.block_idx_last_scheduled_token,
+                    attn_metadata.block_idx_last_scheduled_token[
+                        : num_decodes + num_prefills
+                    ],
                     [num_decodes, num_prefills],
                     dim=0,
                 )
diff --git a/vllm/model_executor/models/nemotron_h_mtp.py b/vllm/model_executor/models/nemotron_h_mtp.py
index ce927f8e2c7f..f454ba433442 100644
--- a/vllm/model_executor/models/nemotron_h_mtp.py
+++ b/vllm/model_executor/models/nemotron_h_mtp.py
@@ -290,7 +290,6 @@ class NemotronHMTP(nn.Module, SupportsPP):
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()
         config = vllm_config.model_config.hf_config
-        cache_config = vllm_config.cache_config
         self.vllm_config = vllm_config
         self.config = config
         self.quant_config = vllm_config.quant_config
@@ -305,10 +304,6 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
                 vllm_config.parallel_config.eplb_config.num_redundant_experts
             )
 
-        assert not cache_config.enable_prefix_caching, (
-            "NemotronHMTP currently does not support prefix caching"
-        )
-
         # MTP predictor
         self.model = NemotronHMultiTokenPredictor(
             vllm_config=vllm_config, prefix=maybe_prefix(prefix, "model")
diff --git a/vllm/v1/attention/backends/mamba2_attn.py b/vllm/v1/attention/backends/mamba2_attn.py
index 4957df7ad66a..f451b8395744 100644
--- a/vllm/v1/attention/backends/mamba2_attn.py
+++ b/vllm/v1/attention/backends/mamba2_attn.py
@@ -375,17 +375,27 @@ def build(
                     device=common_attn_metadata.query_start_loc.device,
                 )
 
-                spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
-                    :, : self.num_spec + 1
-                ]
+                if self.vllm_config.cache_config.enable_prefix_caching:
+                    num_cacheable_blocks = num_computed_tokens // mamba_block_size
+                    block_indices = num_cacheable_blocks.unsqueeze(1) + torch.arange(
+                        self.num_spec + 1, device=self.device
+                    ).unsqueeze(0)
+                    batch_indices = torch.arange(
+                        common_attn_metadata.block_table_tensor.size(0),
+                        device=self.device,
+                    ).unsqueeze(1)
+                    spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
+                        batch_indices, block_indices
+                    ]
+                else:
+                    spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
+                        :, : self.num_spec + 1
+                    ]
                 non_spec_state_indices_tensor = None
                 spec_query_start_loc = common_attn_metadata.query_start_loc
                 non_spec_query_start_loc = None
             else:
                 if self.vllm_config.cache_config.enable_prefix_caching:
-                    block_idx_first_scheduled_token = block_idx_first_scheduled_token[
-                        ~spec_sequence_masks
-                    ]
                     block_idx_last_scheduled_token = block_idx_last_scheduled_token[
                         ~spec_sequence_masks
                     ]
@@ -401,14 +411,24 @@ def build(
                 non_spec_token_indx = index[:num_non_spec_tokens]
                 spec_token_indx = index[num_non_spec_tokens:]
 
-                spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
-                    spec_sequence_masks, : self.num_spec + 1
-                ]
                 if self.vllm_config.cache_config.enable_prefix_caching:
+                    num_cacheable_blocks = num_computed_tokens // mamba_block_size
+                    block_indices = num_cacheable_blocks[spec_sequence_masks].unsqueeze(
+                        1
+                    ) + torch.arange(self.num_spec + 1, device=self.device).unsqueeze(0)
+                    batch_indices = torch.arange(
+                        spec_sequence_masks.sum().item(), device=self.device
+                    ).unsqueeze(1)
+                    spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
+                        spec_sequence_masks
+                    ][batch_indices, block_indices]
                     non_spec_state_indices_tensor = (
                         common_attn_metadata.block_table_tensor[~spec_sequence_masks]
                     )
                 else:
+                    spec_state_indices_tensor = common_attn_metadata.block_table_tensor[
+                        spec_sequence_masks, : self.num_spec + 1
+                    ]
                     non_spec_state_indices_tensor = (
                         common_attn_metadata.block_table_tensor[~spec_sequence_masks, 0]
                     )
@@ -450,7 +470,8 @@ def build(
                 common_attn_metadata.query_start_loc.device
             )
 
-            # Subtract ALL decode tokens (spec + non-spec) to get prefill-only coordinates
+            # Subtract ALL decode tokens (spec + non-spec)
+            # to get prefill-only coordinates
             total_decode_tokens = num_decode_tokens + num_spec_decode_tokens
             query_start_loc_p = (
                 common_attn_metadata.query_start_loc[-num_prefills - 1 :]
diff --git a/vllm/v1/core/single_type_kv_cache_manager.py b/vllm/v1/core/single_type_kv_cache_manager.py
index d90ec550f766..c60f377bd52f 100644
--- a/vllm/v1/core/single_type_kv_cache_manager.py
+++ b/vllm/v1/core/single_type_kv_cache_manager.py
@@ -645,6 +645,12 @@ def find_longest_cache_hit(
                     computed.append(cached)
                 break  # we just need the last match - early stopping
 
+        # TODO - do we need to pop the last block if use_eagle is True?
+        # With hybrid models, it seems unnecessary,
+        # since it is done in the full attention manager.
+        # Popping again means the last 2 blocks are popped overall,
+        # and the performance is hit hard.
+
         return computed_blocks
 
     def get_num_common_prefix_blocks(self, running_request_id: str) -> int: