Instructions to use zai-org/GLM-5.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/GLM-5.2 with Transformers:

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

pipe = pipeline("text-generation", model="zai-org/GLM-5.2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-5.2")
model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-5.2")
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 Settings

vLLM

How to use zai-org/GLM-5.2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/GLM-5.2"
# 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-5.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/GLM-5.2

SGLang

How to use zai-org/GLM-5.2 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-5.2" \
    --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-5.2",
		"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-5.2" \
        --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-5.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zai-org/GLM-5.2 with Docker Model Runner:
```
docker model run hf.co/zai-org/GLM-5.2
```

davidlvxin commited on 17 days ago

Commit

4d67f66

verified ·

1 Parent(s): 120edc2

Update README.md

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -44,7 +44,7 @@ We're introducing GLM-5.2, our latest flagship model for long-horizon tasks. It
 |Reasoning|||||||||||
 |HLE|40.5|31|41.4|37|37.7|49.8*|41.4*|45|
 |HLE (w/ Tools)|54.7|52.3|53.5|-|48.2|57.9*|52.2*|51.4*|
-|CritPt|16.7|4.6|13.4|3.7|12.9|20.9|27.1|17.7|
 |AIME 2026|99.2|95.3|97|-|94.6|95.7|98.3|98.2|
 |HMMT Nov. 2025|94.4|94|95|84.4|94.4|96.5|96.5|94.8|
 |HMMT Feb. 2026|92.5|82.6|97.1|84.4|95.2|96.7|96.7|87.3|

 |Reasoning|||||||||||
 |HLE|40.5|31|41.4|37|37.7|49.8*|41.4*|45|
 |HLE (w/ Tools)|54.7|52.3|53.5|-|48.2|57.9*|52.2*|51.4*|
+|CritPt|20.9|4.6|13.4|3.7|12.9|20.9|27.1|17.7|
 |AIME 2026|99.2|95.3|97|-|94.6|95.7|98.3|98.2|
 |HMMT Nov. 2025|94.4|94|95|84.4|94.4|96.5|96.5|94.8|
 |HMMT Feb. 2026|92.5|82.6|97.1|84.4|95.2|96.7|96.7|87.3|