diff --git a/docs/source/tutorials/multi_npu_quantization.md b/docs/source/tutorials/multi_npu_quantization.md
index 9570804..6360dca 100644
--- a/docs/source/tutorials/multi_npu_quantization.md
+++ b/docs/source/tutorials/multi_npu_quantization.md
@@ -67,7 +67,7 @@ The converted model files looks like:
 `-- tokenizer_config.json
 ```
 
-Run the following script to start the vLLM server with quantize model:
+Run the following script to start the vLLM server with quantized model:
 
 :::{note}
 The value "ascend" for "--quantization" argument will be supported after [a specific PR](https://github.com/vllm-project/vllm-ascend/pull/877) is merged and released, you can cherry-pick this commit for now.
@@ -89,3 +89,46 @@ curl http://localhost:8000/v1/completions \
         "temperature": "0.0"
     }'
 ```
+
+Run the following script to execute offline inference on multi-NPU with quantized model:
+
+:::{note}
+To enable quantization for ascend, quantization method must be "ascend" 
+:::
+
+```python
+import gc
+
+import torch
+
+from vllm import LLM, SamplingParams
+from vllm.distributed.parallel_state import (destroy_distributed_environment,
+                                             destroy_model_parallel)
+
+def clean_up():
+    destroy_model_parallel()
+    destroy_distributed_environment()
+    gc.collect()
+    torch.npu.empty_cache()
+
+prompts = [
+    "Hello, my name is",
+    "The future of AI is",
+]
+sampling_params = SamplingParams(temperature=0.6, top_p=0.95, top_k=40)
+
+llm = LLM(model="/home/models/QwQ-32B-w8a8",
+          tensor_parallel_size=4,
+          distributed_executor_backend="mp",
+          max_model_len=4096,
+          quantization="ascend")
+
+outputs = llm.generate(prompts, sampling_params)
+for output in outputs:
+    prompt = output.prompt
+    generated_text = output.outputs[0].text
+    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+
+del llm
+clean_up()
+```
\ No newline at end of file