Instructions to use Qwen/Qwen3-30B-A3B-Thinking-2507 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/Qwen3-30B-A3B-Thinking-2507 with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/Qwen3-30B-A3B-Thinking-2507")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-30B-A3B-Thinking-2507")
model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen3-30B-A3B-Thinking-2507")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Qwen/Qwen3-30B-A3B-Thinking-2507 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/Qwen3-30B-A3B-Thinking-2507"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Qwen/Qwen3-30B-A3B-Thinking-2507",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen3-30B-A3B-Thinking-2507

SGLang

How to use Qwen/Qwen3-30B-A3B-Thinking-2507 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 "Qwen/Qwen3-30B-A3B-Thinking-2507" \
    --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": "Qwen/Qwen3-30B-A3B-Thinking-2507",
		"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 "Qwen/Qwen3-30B-A3B-Thinking-2507" \
        --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": "Qwen/Qwen3-30B-A3B-Thinking-2507",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen3-30B-A3B-Thinking-2507 with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen3-30B-A3B-Thinking-2507
```

Adding response schema

#11

by Rocketknight1 HF Staff - opened Oct 24, 2025

base: refs/heads/main

←

from: refs/pr/11

Discussion Files changed

+354

-249

Upload tokenizer38506e69

Rocketknight1

Oct 24, 2025

•

edited Oct 30, 2025

This PR adds a response schema to Qwen3-30B-A3B, which means that model outputs can automatically be parsed!

It also updates the chat template to accept reasoning as a key for chain-of-thought data. reasoning_content is still supported, so this PR should not have any effect on backward compatibility! We want to standardize so that all models can accept reasoning, even if they also accept other names too.

Revert unnecessary extra changes from save_pretrained7c4c459f

Rocketknight1 changed pull request title from Upload tokenizer to Adding response schema Oct 24, 2025

Update README.md8217eea0

Update README.md437b1324

Update tokenizer_config.json3ca25493

Update tokenizer_config.json8a493793

Update README.md3e892879

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