Instructions to use zai-org/GLM-4.6V-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/GLM-4.6V-Flash with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="zai-org/GLM-4.6V-Flash")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("zai-org/GLM-4.6V-Flash")
model = AutoModelForImageTextToText.from_pretrained("zai-org/GLM-4.6V-Flash")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/GLM-4.6V-Flash with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/GLM-4.6V-Flash"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4.6V-Flash",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/GLM-4.6V-Flash

SGLang

How to use zai-org/GLM-4.6V-Flash with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zai-org/GLM-4.6V-Flash" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4.6V-Flash",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zai-org/GLM-4.6V-Flash" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4.6V-Flash",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use zai-org/GLM-4.6V-Flash with Docker Model Runner:
```
docker model run hf.co/zai-org/GLM-4.6V-Flash
```

VLLM 启动报错了

#20

by qinghuiyyds - opened Dec 15, 2025

Discussion

qinghuiyyds

Dec 15, 2025

(EngineCore_DP0 pid=1717473) File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/transformers_utils/processor.py", line 154, in get_processor
(EngineCore_DP0 pid=1717473) raise TypeError(
(EngineCore_DP0 pid=1717473) TypeError: Invalid type of HuggingFace processor. Expected type: <class 'transformers.processing_utils.ProcessorMixin'>, but found type: <class 'transformers.tokenization_utils_fast.PreTrainedTokenizerFast'>
Traceback (most recent call last):
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/entrypoints/api_server.py", line 184, in
asyncio.run(run_server(args))
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
return future.result()
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/entrypoints/api_server.py", line 132, in run_server
app = await init_app(args, llm_engine)
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/entrypoints/api_server.py", line 116, in init_app
else AsyncLLMEngine.from_engine_args(
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/async_llm.py", line 232, in from_engine_args
return cls(
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/async_llm.py", line 133, in init
self.engine_core = EngineCoreClient.make_async_mp_client(
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/core_client.py", line 121, in make_async_mp_client
return AsyncMPClient(*client_args)
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/core_client.py", line 808, in init
super().init(
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/core_client.py", line 469, in init
with launch_core_engines(vllm_config, executor_class, log_stats) as (
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/contextlib.py", line 142, in exit
next(self.gen)
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/utils.py", line 907, in launch_core_engines
wait_for_engine_startup(
File "/home/xiandai/miniconda3/envs/glm_vl/lib/python3.10/site-packages/vllm/v1/engine/utils.py", line 964, in wait_for_engine_startup
raise RuntimeError(
RuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}

tuo02

Dec 19, 2025

transformer 版本换成 5.0.0rc0 可以起服务，但是对于多模态的请求不能正常响应

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