diff --git a/vllm_ascend/platform.py b/vllm_ascend/platform.py
index 6bcad2c..4a2b099 100644
--- a/vllm_ascend/platform.py
+++ b/vllm_ascend/platform.py
@@ -32,7 +32,7 @@ from vllm_ascend.ascend_config import (check_ascend_config, get_ascend_config,
 from vllm_ascend.torchair.utils import (check_torchair_cache_exist,
                                         delete_torchair_cache_file)
 from vllm_ascend.utils import (ASCEND_QUANTIZATION_METHOD, enable_sp, is_310p,
-                               update_aclgraph_sizes,
+                               is_vl_model, update_aclgraph_sizes,
                                update_default_aclgraph_sizes)
 
 if TYPE_CHECKING:
@@ -303,6 +303,14 @@ class NPUPlatform(Platform):
                 vllm_config.scheduler_config)
             vllm_config.scheduler_config = recompute_scheduler_config
 
+        if is_vl_model(vllm_config):
+            if bool(int(os.getenv("VLLM_ASCEND_ENABLE_FLASHCOMM", '0'))) or \
+               bool(int(os.getenv("VLLM_ASCEND_ENABLE_FLASHCOMM1", '0'))):
+                raise ValueError(
+                    "Currently, VL models doesn't support "
+                    "FLASHCOMM in vllm-ascend. We will fix this in the future. "
+                    "Please set VLLM_ASCEND_ENABLE_FLASHCOMM1=0.")
+
     @classmethod
     def get_attn_backend_cls(
         cls,
diff --git a/vllm_ascend/utils.py b/vllm_ascend/utils.py
index 8f21ef7..52a88ec 100644
--- a/vllm_ascend/utils.py
+++ b/vllm_ascend/utils.py
@@ -57,6 +57,7 @@ _ASCEND_CUSTOMOP_IS_REIGISTERED = False
 _DEFAULT_BUFFER_SIZE = 200
 _MIN_DP_BUFFER_SIZE = 50
 _IS_MOE_MODEL = None
+_IS_VL_MODEL = None
 _ENABLE_SP = None
 _HAS_LAYER_IDX = None
 _ENABLE_NZ = None
@@ -696,6 +697,15 @@ def _is_contain_expert(config: Any):
     return False
 
 
+def is_vl_model(vllm_config: VllmConfig):
+    """Checks if the model is a VL model by config"""
+    global _IS_VL_MODEL
+    if _IS_VL_MODEL is None:
+        model_configs = vllm_config.model_config.hf_config.to_dict()
+        _IS_VL_MODEL = "VL" in model_configs["architectures"][0]
+    return _IS_VL_MODEL
+
+
 def weak_ref_tensor(tensor: Any) -> Any:
     """
     Create a weak reference to a tensor.