diff --git a/vllm/model_executor/models/kimi_k25.py b/vllm/model_executor/models/kimi_k25.py
index bb9f35bdb..9d287ba9b 100644
--- a/vllm/model_executor/models/kimi_k25.py
+++ b/vllm/model_executor/models/kimi_k25.py
@@ -23,6 +23,10 @@ from transformers.processing_utils import ProcessorMixin
 from vllm.config import VllmConfig
 from vllm.config.multimodal import BaseDummyOptions
 from vllm.logger import init_logger
+from vllm.model_executor.layers.quantization import QuantizationConfig
+from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors import (
+    CompressedTensorsConfig,
+)
 from vllm.model_executor.models.interfaces import (
     SupportsMultiModal,
     SupportsPP,
@@ -361,6 +365,7 @@ class KimiK25ForConditionalGeneration(
         with self._mark_tower_model(vllm_config, "vision_chunk"):
             self.vision_tower = MoonViT3dPretrainedModel(
                 config.vision_config,
+                quant_config=self._maybe_ignore_quant_config(quant_config),
                 prefix=maybe_prefix(prefix, "vision_tower"),
             )
             self.vision_tower = self.vision_tower.to(
@@ -370,6 +375,7 @@ class KimiK25ForConditionalGeneration(
             self.mm_projector = KimiK25MultiModalProjector(
                 config=config.vision_config,
                 use_data_parallel=self.use_data_parallel,
+                quant_config=self._maybe_ignore_quant_config(quant_config),
                 prefix=maybe_prefix(prefix, "mm_projector"),
             )
             self.mm_projector = self.mm_projector.to(
@@ -389,6 +395,11 @@ class KimiK25ForConditionalGeneration(
         )
         self.media_placeholder: int = self.config.media_placeholder_token_id
 
+    def _maybe_ignore_quant_config(self, quant_config: QuantizationConfig):
+        if isinstance(quant_config, CompressedTensorsConfig):
+            return None
+        return quant_config
+
     def _parse_and_validate_media_input(
         self, **kwargs: object
     ) -> KimiK25MediaPixelInputs | None:
diff --git a/vllm/model_executor/models/kimi_k25_vit.py b/vllm/model_executor/models/kimi_k25_vit.py
index 470311ecc..69524293c 100644
--- a/vllm/model_executor/models/kimi_k25_vit.py
+++ b/vllm/model_executor/models/kimi_k25_vit.py
@@ -28,6 +28,7 @@ from vllm.model_executor.layers.linear import (
     ReplicatedLinear,
     RowParallelLinear,
 )
+from vllm.model_executor.layers.quantization import QuantizationConfig
 from vllm.model_executor.models.utils import maybe_prefix
 from vllm.model_executor.models.vision import (
     is_vit_use_data_parallel,
@@ -304,6 +305,7 @@ class MLP2(nn.Module):
         dims: list[int],
         activation,
         bias: bool = True,
+        quant_config: QuantizationConfig | None = None,
         prefix: str = "",
         use_data_parallel: bool = False,
     ):
@@ -314,6 +316,7 @@ class MLP2(nn.Module):
             dims[0],
             dims[1],
             bias=bias,
+            quant_config=quant_config,
             prefix=maybe_prefix(prefix, "fc0"),
             disable_tp=self.use_data_parallel,
         )
@@ -321,6 +324,7 @@ class MLP2(nn.Module):
             dims[1],
             dims[2],
             bias=bias,
+            quant_config=quant_config,
             prefix=maybe_prefix(prefix, "fc1"),
             disable_tp=self.use_data_parallel,
         )
@@ -341,6 +345,7 @@ class MoonViTEncoderLayer(nn.Module):
         num_heads: int,
         hidden_dim: int,
         mlp_dim: int,
+        quant_config: QuantizationConfig | None = None,
         prefix: str = "",
         *,
         activation=F.gelu,
@@ -362,6 +367,7 @@ class MoonViTEncoderLayer(nn.Module):
         self.mlp = MLP2(
             [hidden_dim, mlp_dim, hidden_dim],
             activation,
+            quant_config=quant_config,
             prefix=f"{prefix}.mlp",
             use_data_parallel=self.use_data_parallel,
         )
@@ -371,6 +377,7 @@ class MoonViTEncoderLayer(nn.Module):
             total_num_heads=num_heads,
             total_num_kv_heads=num_heads,
             bias=attn_bias,
+            quant_config=quant_config,
             prefix=f"{prefix}.wqkv",
             disable_tp=self.use_data_parallel,
         )
@@ -378,6 +385,7 @@ class MoonViTEncoderLayer(nn.Module):
             hidden_dim,
             hidden_dim,
             bias=attn_bias,
+            quant_config=quant_config,
             prefix=f"{prefix}.wo",
             disable_tp=self.use_data_parallel,
         )
@@ -461,6 +469,7 @@ class MoonViT3dEncoder(nn.Module):
         num_layers: int,
         block_cfg: dict,
         video_attn_type: str = "spatial_temporal",
+        quant_config: QuantizationConfig | None = None,
         prefix: str = "",
     ) -> None:
         super().__init__()
@@ -476,6 +485,7 @@ class MoonViT3dEncoder(nn.Module):
             [
                 MoonViTEncoderLayer(
                     **block_cfg,
+                    quant_config=quant_config,
                     prefix=f"{prefix}.blocks.{layer_idx}",
                 )
                 for layer_idx in range(num_layers)
@@ -544,6 +554,7 @@ class MoonViT3dPretrainedModel(nn.Module):
     def __init__(
         self,
         config: KimiK25VisionConfig,
+        quant_config: QuantizationConfig | None = None,
         prefix: str = "",
     ):
         super().__init__()
@@ -573,6 +584,7 @@ class MoonViT3dPretrainedModel(nn.Module):
                 "attn_bias": True,
             },
             video_attn_type=config.video_attn_type,
+            quant_config=quant_config,
             prefix=maybe_prefix(prefix, "encoder"),
         )
 
@@ -646,6 +658,7 @@ class KimiK25MultiModalProjector(nn.Module):
         self,
         config: KimiK25VisionConfig,
         use_data_parallel: bool = False,
+        quant_config: QuantizationConfig | None = None,
         prefix: str = "",
     ):
         super().__init__()
@@ -660,12 +673,14 @@ class KimiK25MultiModalProjector(nn.Module):
             self.hidden_size,
             self.hidden_size,
             bias=True,
+            quant_config=quant_config,
             prefix=f"{prefix}.linear_1",
         )
         self.linear_2 = ReplicatedLinear(
             self.hidden_size,
             config.mm_hidden_size,
             bias=True,
+            quant_config=quant_config,
             prefix=f"{prefix}.linear_2",
         )
         self.act = GELUActivation()