diff --git a/tests/st/python/cases_parallel/vllm_qwen2_5_vl_7b_v1.py b/tests/st/python/cases_parallel/vllm_qwen2_5_vl_7b_v1.py
index daffc4782158015008df32c2ea7a757e211e39ba..5dcf3030025109f9bd30baddbf5185491db2b7b6 100644
--- a/tests/st/python/cases_parallel/vllm_qwen2_5_vl_7b_v1.py
+++ b/tests/st/python/cases_parallel/vllm_qwen2_5_vl_7b_v1.py
@@ -52,6 +52,12 @@ PROMPT_TEMPLATE = (
     "What is in the image?<|im_end|>\n"
     "<|im_start|>assistant\n")
 
+PROMPT_TEMPLATE_2 = (
+    "<|im_start|>system\nYou are a helpful assistant.<|im_end|>"
+    "\n<|im_start|>user\n<|vision_start|><|image_pad|><|vision_end|>"
+    "Is there anyone in the picture?<|im_end|>\n"
+    "<|im_start|>assistant\n")
+
 video_path = "/home/workspace/mindspore_dataset/video_file/korean_eating.mp4"
 model_path = "/home/workspace/mindspore_dataset/weight/Qwen2.5-VL-7B-Instruct"
 
@@ -75,12 +81,20 @@ def generate_llm_engine(enforce_eager=False, tensor_parallel_size=1):
 
 
 def forward_and_check(llm):
-    inputs = [{
-        "prompt": PROMPT_TEMPLATE,
-        "multi_modal_data": {
-            "image": pil_image()
+    inputs = [
+        {
+            "prompt": PROMPT_TEMPLATE,
+            "multi_modal_data": {
+                "image": pil_image()
+            },
         },
-    }]
+        {
+            "prompt": PROMPT_TEMPLATE_2,
+            "multi_modal_data": {
+                "image": pil_image()
+            },
+        },
+    ]
 
     # Create a sampling params object.
     sampling_params = SamplingParams(temperature=0.0, max_tokens=128, top_k=1)
diff --git a/vllm_mindspore/model_executor/models/registry.py b/vllm_mindspore/model_executor/models/registry.py
index f3564e0f220f6499aaae8e0e906efabf3e0aec1d..cd6d92537e09913dfc93a911e3e27034a5af381a 100644
--- a/vllm_mindspore/model_executor/models/registry.py
+++ b/vllm_mindspore/model_executor/models/registry.py
@@ -38,7 +38,8 @@ try:
         if name.startswith("mcore_")
     ]
 except ImportError as e:
-    logger.warning("Error when importing MindSpore Transformers: %s", e)
+    logger.info("Can't get model support list from MindSpore Transformers: %s",
+                e)
     if is_mindformers_model_backend():
         raise ImportError from e
     mf_supported = False
@@ -48,7 +49,7 @@ try:
     from mindone import transformers  # noqa: F401
     mindone_supported = True
 except ImportError as e:
-    logger.warning("Error when importing MindSpore ONE: %s", e)
+    logger.info("No MindSpore ONE: %s", e)
     if is_mindone_model_backend():
         raise ImportError from e
     mindone_supported = False
diff --git a/vllm_mindspore/platforms/ascend.py b/vllm_mindspore/platforms/ascend.py
index 8e39c3d1560d7de3b653ac22eefd5fdc51cbd3ea..0df8f3e8548f829157c408c3db2fa0923c4b7727 100644
--- a/vllm_mindspore/platforms/ascend.py
+++ b/vllm_mindspore/platforms/ascend.py
@@ -100,7 +100,8 @@ class AscendPlatform(Platform):
 
         cache_config = vllm_config.cache_config
         if cache_config and cache_config.block_size is None:
-            cache_config.block_size = 16
+            # default value: 16 -> 128 for better performance
+            cache_config.block_size = 128
 
         model_config = vllm_config.model_config
         model_config.disable_cascade_attn = True