diff --git a/vllm/model_executor/layers/attention/chunked_local_attention.py b/vllm/model_executor/layers/attention/chunked_local_attention.py
index cb595438ad..72aad84781 100644
--- a/vllm/model_executor/layers/attention/chunked_local_attention.py
+++ b/vllm/model_executor/layers/attention/chunked_local_attention.py
@@ -20,7 +20,6 @@ from vllm.v1.attention.backends.utils import (
 )
 from vllm.v1.attention.selector import get_attn_backend
 from vllm.v1.kv_cache_interface import (
-    AttentionSpec,
     ChunkedLocalAttentionSpec,
     KVCacheSpec,
     get_kv_quant_mode,
@@ -42,7 +41,7 @@ def create_chunked_local_attention_backend(
         def get_cudagraph_support(
             cls: type["AttentionMetadataBuilder"],
             vllm_config: VllmConfig,
-            kv_cache_spec: AttentionSpec,
+            kv_cache_spec: KVCacheSpec,
         ) -> AttentionCGSupport:
             # Explicit override in case the underlying builder specialized this getter.
             # @override omitted only because of mypy limitation due to type variable.
diff --git a/vllm/model_executor/layers/attention/mla_attention.py b/vllm/model_executor/layers/attention/mla_attention.py
index 4a265554b7..5292dd9c9a 100644
--- a/vllm/model_executor/layers/attention/mla_attention.py
+++ b/vllm/model_executor/layers/attention/mla_attention.py
@@ -1722,6 +1722,8 @@ class MLACommonMetadataBuilder(AttentionMetadataBuilder[M]):
     understand this class
     """
 
+    kv_cache_spec: AttentionSpec
+
     # Defines the level of query length support for this backend.
     # - SINGLE_ONLY: Only single-token queries (no spec decode support)
     # - UNIFORM: Supports uniform multi-token queries (spec decode with uniform lengths)
diff --git a/vllm/v1/attention/backend.py b/vllm/v1/attention/backend.py
index b5d8962fd4..6f2ddd31f8 100644
--- a/vllm/v1/attention/backend.py
+++ b/vllm/v1/attention/backend.py
@@ -25,7 +25,7 @@ if TYPE_CHECKING:
     from vllm.model_executor.layers.quantization.utils.quant_utils import QuantKey
     from vllm.platforms.interface import DeviceCapability
     from vllm.v1.attention.backends.utils import KVCacheLayoutType
-    from vllm.v1.kv_cache_interface import AttentionSpec, KVQuantMode
+    from vllm.v1.kv_cache_interface import KVCacheSpec, KVQuantMode
 
 from vllm.v1.kv_cache_interface import get_kv_quant_mode
 
@@ -635,7 +635,7 @@ class AttentionMetadataBuilder(ABC, Generic[M]):
     @abstractmethod
     def __init__(
         self,
-        kv_cache_spec: "AttentionSpec",
+        kv_cache_spec: "KVCacheSpec",
         layer_names: list[str],
         vllm_config: "VllmConfig",
         device: torch.device,
@@ -649,7 +649,7 @@ class AttentionMetadataBuilder(ABC, Generic[M]):
     def get_cudagraph_support(
         cls: type["AttentionMetadataBuilder"],
         vllm_config: "VllmConfig",
-        kv_cache_spec: "AttentionSpec",
+        kv_cache_spec: "KVCacheSpec",
     ) -> AttentionCGSupport:
         """Get the cudagraph support level of this builder class."""
         return cls._cudagraph_support
diff --git a/vllm/v1/attention/backends/flash_attn.py b/vllm/v1/attention/backends/flash_attn.py
index 416377deab..6e5c8d7f24 100755
--- a/vllm/v1/attention/backends/flash_attn.py
+++ b/vllm/v1/attention/backends/flash_attn.py
@@ -58,7 +58,7 @@ from vllm.v1.attention.backend import (
     CommonAttentionMetadata,
 )
 from vllm.v1.attention.backends.utils import get_kv_cache_layout
-from vllm.v1.kv_cache_interface import AttentionSpec
+from vllm.v1.kv_cache_interface import AttentionSpec, KVCacheSpec
 from vllm.v1.worker.cp_utils import (
     run_split_fa2_dcp_context_attention,
     should_skip_dcp_context_attention,
@@ -360,7 +360,7 @@ class FlashAttentionMetadataBuilder(AttentionMetadataBuilder[FlashAttentionMetad
     def get_cudagraph_support(
         cls,
         vllm_config: "VllmConfig",
-        kv_cache_spec: "AttentionSpec",
+        kv_cache_spec: "KVCacheSpec",
     ) -> AttentionCGSupport:
         return cls._cudagraph_support
 
diff --git a/vllm/v1/attention/backends/flashinfer.py b/vllm/v1/attention/backends/flashinfer.py
index 5a02974724..5251e25e5e 100755
--- a/vllm/v1/attention/backends/flashinfer.py
+++ b/vllm/v1/attention/backends/flashinfer.py
@@ -76,6 +76,7 @@ from vllm.v1.attention.ops.dcp_alltoall import dcp_a2a_lse_reduce
 from vllm.v1.attention.ops.merge_attn_states import merge_attn_states
 from vllm.v1.kv_cache_interface import (
     AttentionSpec,
+    KVCacheSpec,
     KVQuantMode,
     UniformTypeKVCacheSpecs,
 )
@@ -617,6 +618,7 @@ class FlashInferMetadata:
 
 
 class FlashInferMetadataBuilder(AttentionMetadataBuilder[FlashInferMetadata]):
+    kv_cache_spec: AttentionSpec
     reorder_batch_threshold: int = 1
 
     def __init__(
@@ -893,7 +895,7 @@ class FlashInferMetadataBuilder(AttentionMetadataBuilder[FlashInferMetadata]):
     def get_cudagraph_support(
         cls: type["FlashInferMetadataBuilder"],
         vllm_config: VllmConfig,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: KVCacheSpec,
     ) -> AttentionCGSupport:
         """Get the cudagraph support level for FlashInfer attention.
 
diff --git a/vllm/v1/attention/backends/gdn_attn.py b/vllm/v1/attention/backends/gdn_attn.py
index 70794be075..0b32dfcf94 100644
--- a/vllm/v1/attention/backends/gdn_attn.py
+++ b/vllm/v1/attention/backends/gdn_attn.py
@@ -21,7 +21,7 @@ from vllm.v1.attention.backends.utils import (
     mamba_get_block_table_tensor,
     split_decodes_and_prefills,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec, MambaSpec
+from vllm.v1.kv_cache_interface import MambaSpec
 
 
 class GDNAttentionBackend(AttentionBackend):
@@ -80,18 +80,18 @@ class GDNAttentionMetadata:
 
 
 class GDNAttentionMetadataBuilder(AttentionMetadataBuilder[GDNAttentionMetadata]):
+    kv_cache_spec: MambaSpec
     _cudagraph_support = AttentionCGSupport.UNIFORM_BATCH
 
     reorder_batch_threshold: int = 1
 
     def __init__(
         self,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: MambaSpec,
         layer_names: list[str],
         vllm_config: VllmConfig,
         device: torch.device,
     ):
-        assert isinstance(kv_cache_spec, MambaSpec)
         self.vllm_config = vllm_config
         self.compilation_config = vllm_config.compilation_config
         self.speculative_config = vllm_config.speculative_config
diff --git a/vllm/v1/attention/backends/hpc_attn.py b/vllm/v1/attention/backends/hpc_attn.py
index 8c6dcfe516..91422e8eac 100644
--- a/vllm/v1/attention/backends/hpc_attn.py
+++ b/vllm/v1/attention/backends/hpc_attn.py
@@ -33,7 +33,7 @@ from vllm.v1.attention.backends.utils import (
     KVCacheLayoutType,
     split_decodes_and_prefills,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec
+from vllm.v1.kv_cache_interface import AttentionSpec, KVCacheSpec
 
 logger = init_logger(__name__)
 
@@ -158,7 +158,7 @@ class HpcAttnMetadataBuilder(AttentionMetadataBuilder[HpcAttnMetadata]):
     def get_cudagraph_support(
         cls: type["HpcAttnMetadataBuilder"],
         vllm_config: VllmConfig,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: KVCacheSpec,
     ) -> AttentionCGSupport:
         spec_config = vllm_config.speculative_config
         if (
diff --git a/vllm/v1/attention/backends/linear_attn.py b/vllm/v1/attention/backends/linear_attn.py
index 9cdcf0e30e..0831246d67 100644
--- a/vllm/v1/attention/backends/linear_attn.py
+++ b/vllm/v1/attention/backends/linear_attn.py
@@ -16,7 +16,7 @@ from vllm.v1.attention.backends.utils import (
     mamba_get_block_table_tensor,
     split_decodes_and_prefills,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec, MambaSpec
+from vllm.v1.kv_cache_interface import KVCacheSpec, MambaSpec
 
 
 class LinearAttentionBackend(AttentionBackend):
@@ -46,19 +46,19 @@ class LinearAttentionMetadata:
 
 
 class LinearAttentionMetadataBuilder(AttentionMetadataBuilder[LinearAttentionMetadata]):
+    kv_cache_spec: MambaSpec
     reorder_batch_threshold: int = 1
 
     _cudagraph_support = AttentionCGSupport.UNIFORM_SINGLE_TOKEN_DECODE
 
     def __init__(
         self,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: MambaSpec,
         layer_names: list[str],
         vllm_config: VllmConfig,
         device: torch.device,
     ):
         super().__init__(kv_cache_spec, layer_names, vllm_config, device)
-        assert isinstance(kv_cache_spec, MambaSpec)
 
     def build(
         self,
@@ -120,13 +120,13 @@ class BailingLinearAttentionMetadataBuilder(LinearAttentionMetadataBuilder):
     def get_cudagraph_support(
         cls,
         vllm_config: VllmConfig,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: KVCacheSpec,
     ) -> AttentionCGSupport:
         return AttentionCGSupport.UNIFORM_BATCH
 
     def __init__(
         self,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: MambaSpec,
         layer_names: list[str],
         vllm_config: VllmConfig,
         device: torch.device,
diff --git a/vllm/v1/attention/backends/mamba2_attn.py b/vllm/v1/attention/backends/mamba2_attn.py
index 6b4999ab35..30b641bd0d 100644
--- a/vllm/v1/attention/backends/mamba2_attn.py
+++ b/vllm/v1/attention/backends/mamba2_attn.py
@@ -16,7 +16,7 @@ from vllm.v1.attention.backends.mamba_attn import (
     BaseMambaAttentionMetadata,
     BaseMambaAttentionMetadataBuilder,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec
+from vllm.v1.kv_cache_interface import MambaSpec
 
 
 def compute_varlen_chunk_metadata(
@@ -118,7 +118,7 @@ class Mamba2AttentionMetadataBuilder(
 
     def __init__(
         self,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: MambaSpec,
         layer_names: list[str],
         vllm_config: VllmConfig,
         device: torch.device,
diff --git a/vllm/v1/attention/backends/mamba_attn.py b/vllm/v1/attention/backends/mamba_attn.py
index 28928f2894..2a607edd9e 100644
--- a/vllm/v1/attention/backends/mamba_attn.py
+++ b/vllm/v1/attention/backends/mamba_attn.py
@@ -21,7 +21,7 @@ from vllm.v1.attention.backends.utils import (
     mamba_get_block_table_tensor,
     split_decodes_and_prefills,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec, MambaSpec
+from vllm.v1.kv_cache_interface import MambaSpec
 
 M = TypeVar("M", bound="BaseMambaAttentionMetadata")
 
@@ -83,6 +83,7 @@ class BaseMambaAttentionMetadata:
 
 
 class BaseMambaAttentionMetadataBuilder(AttentionMetadataBuilder[M], abc.ABC):
+    kv_cache_spec: MambaSpec
     metadata_cls: type[M]
     reorder_batch_threshold: int = 1
     _cudagraph_support: ClassVar[AttentionCGSupport] = AttentionCGSupport.UNIFORM_BATCH
@@ -92,7 +93,7 @@ class BaseMambaAttentionMetadataBuilder(AttentionMetadataBuilder[M], abc.ABC):
 
     def __init__(
         self,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: MambaSpec,
         layer_names: list[str],
         vllm_config: VllmConfig,
         device: torch.device,
@@ -107,7 +108,6 @@ class BaseMambaAttentionMetadataBuilder(AttentionMetadataBuilder[M], abc.ABC):
         self.use_replayssm = vllm_config.cache_config.use_replayssm
         self.replayssm_buffer_len = vllm_config.cache_config.replayssm_buffer_len
 
-        assert isinstance(kv_cache_spec, MambaSpec)
         scheduler_config = vllm_config.scheduler_config
         self.decode_cudagraph_max_bs: int = scheduler_config.max_num_seqs
         if self.compilation_config.max_cudagraph_capture_size is not None:
diff --git a/vllm/v1/attention/backends/mla/indexer.py b/vllm/v1/attention/backends/mla/indexer.py
index 24ab48ddd0..84692c665f 100644
--- a/vllm/v1/attention/backends/mla/indexer.py
+++ b/vllm/v1/attention/backends/mla/indexer.py
@@ -36,7 +36,7 @@ from vllm.v1.attention.backends.utils import (
     get_dcp_local_seq_lens,
     split_decodes_and_prefills,
 )
-from vllm.v1.kv_cache_interface import AttentionSpec, MLAAttentionSpec
+from vllm.v1.kv_cache_interface import KVCacheSpec, MLAAttentionSpec
 from vllm.v1.worker.cp_utils import get_kv_cache_shard_count
 
 logger = init_logger(__name__)
@@ -463,7 +463,7 @@ class DeepseekV32IndexerMetadataBuilder(AttentionMetadataBuilder):
     def get_cudagraph_support(
         cls,
         vllm_config: VllmConfig,
-        kv_cache_spec: AttentionSpec,
+        kv_cache_spec: KVCacheSpec,
     ) -> AttentionCGSupport:
         return AttentionCGSupport.UNIFORM_BATCH
 
diff --git a/vllm/v1/attention/backends/turboquant_attn.py b/vllm/v1/attention/backends/turboquant_attn.py
index a274339afc..981aa9b32a 100644
--- a/vllm/v1/attention/backends/turboquant_attn.py
+++ b/vllm/v1/attention/backends/turboquant_attn.py
@@ -53,6 +53,7 @@ from vllm.v1.attention.ops.triton_turboquant_decode import (
     triton_turboquant_decode_attention,
 )
 from vllm.v1.attention.ops.triton_turboquant_store import triton_turboquant_store
+from vllm.v1.kv_cache_interface import AttentionSpec
 from vllm.v1.worker.workspace import (
     current_workspace_manager,
     is_workspace_manager_initialized,
@@ -198,6 +199,7 @@ class TurboQuantMetadata(AttentionMetadata):
 class TurboQuantMetadataBuilder(AttentionMetadataBuilder[TurboQuantMetadata]):
     """Builds TurboQuantMetadata from scheduler output."""
 
+    kv_cache_spec: AttentionSpec
     _cudagraph_support: ClassVar[AttentionCGSupport] = AttentionCGSupport.UNIFORM_BATCH
 
     def __init__(self, kv_cache_spec, layer_names, vllm_config, device):
diff --git a/vllm/v1/worker/gpu/attn_utils.py b/vllm/v1/worker/gpu/attn_utils.py
index 7dff4cbe4c..d346a42127 100644
--- a/vllm/v1/worker/gpu/attn_utils.py
+++ b/vllm/v1/worker/gpu/attn_utils.py
@@ -169,7 +169,7 @@ def init_attn_backend(
             # Check cudagraph support for the attention backend
             cg_support = builder.get_cudagraph_support(
                 vllm_config,
-                cast(AttentionSpec, group.kv_cache_spec),
+                group.kv_cache_spec,
             )
             if cg_support.value < min_cg_support.value:
                 min_cg_support = cg_support
diff --git a/vllm/v1/worker/gpu/model_states/encoder_only.py b/vllm/v1/worker/gpu/model_states/encoder_only.py
index 91664b211e..cf89183179 100644
--- a/vllm/v1/worker/gpu/model_states/encoder_only.py
+++ b/vllm/v1/worker/gpu/model_states/encoder_only.py
@@ -1,6 +1,6 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-from typing import Any, cast
+from typing import Any
 
 import torch
 import torch.nn as nn
@@ -15,11 +15,7 @@ from vllm.v1.attention.backend import (
     CommonAttentionMetadata,
 )
 from vllm.v1.core.sched.output import NewRequestData
-from vllm.v1.kv_cache_interface import (
-    AttentionSpec,
-    EncoderOnlyAttentionSpec,
-    KVCacheConfig,
-)
+from vllm.v1.kv_cache_interface import EncoderOnlyAttentionSpec, KVCacheConfig
 from vllm.v1.worker.gpu.input_batch import InputBatch
 from vllm.v1.worker.gpu.mm.encoder_cache import EncoderCache
 from vllm.v1.worker.gpu.model_states.default import DefaultModelState
@@ -152,7 +148,7 @@ class EncoderOnlyModelState(DefaultModelState):
         for group in self.encoder_attn_groups:
             builder = group.get_metadata_builder(0)
             cg_support = builder.get_cudagraph_support(
-                self.vllm_config, cast(AttentionSpec, group.kv_cache_spec)
+                self.vllm_config, group.kv_cache_spec
             )
             if cg_support.value < support.value:
                 support = cg_support