Instructions to use zai-org/GLM-5.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/GLM-5.1 with Transformers:

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

pipe = pipeline("text-generation", model="zai-org/GLM-5.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-5.1")
model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-5.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/GLM-5.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/GLM-5.1"
# 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-5.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/GLM-5.1

SGLang

How to use zai-org/GLM-5.1 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-5.1" \
    --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-5.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-5.1" \
        --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-5.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zai-org/GLM-5.1 with Docker Model Runner:
```
docker model run hf.co/zai-org/GLM-5.1
```

GLM5.1角色问题-重要

#17

by liuyt6515 - opened Apr 10

Discussion

liuyt6515

Apr 10

我在进行豆包专家模式与智普5.1进行技术碰撞时，出现了如下情况：GLM5.1认为自己是chatgpt

liuyt6515

Apr 10

liuyt6515

Apr 10

hebangwen

Apr 10

DeepSeek V3“报错家门”：我是ChatGPT

CHNtentes

Apr 11

这还是2026年吗，给我干哪来了

lanesun

Apr 11

如果是对应 APP 的系统提示的话，提 Issue 给对应的 APP，如果是想说模型的蒸馏什么的问题的话，个人观点，省省吧，性能好就行，管它什么地缘政治，问问 OpenAI 以外的随便哪个开源的模型开发者：如果你制作的模型因为输出有 ChatGPT 就一直被别人挑说抄袭抄袭，你心情好不好？在智谱到底有没有蒸馏之前，这是站位的问题：还想不想要好的开源模型了？OpenAI 没有给我们大家钱，原本的目标也是垄断，在 HF 社区对这种问题提意见，本质上来说就是和所有开源模型工作者叫板，或许你也不是坏心，但哪怕你去和 GLM 私发或是随便去哪里评论，不要在 HF 上面这么说，给你提个醒，不如说，最好 HF 上再也不要有这类言论了。

实话说，本来我是根本不可能对这种 Issue 评论的，本来也很少评论，但转念一想，万一 HF 上面大家都慢慢带节奏，火上浇油，最后就和 OpenAI、Google、Anthropic 想要的一样，给商模立法知识产权，简单想象一下，那结果会怎样？LLM 大概率会变成和音视频编码器一样的专利泥潭，你敢做免费模型给大家用？不用怕，告死你。

这就是像你这样发这种 Issue 所会引向的未来。