Instructions to use Qwen/Qwen3-VL-235B-A22B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen3-VL-235B-A22B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Qwen/Qwen3-VL-235B-A22B-Instruct") 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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-235B-A22B-Instruct") model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen3-VL-235B-A22B-Instruct") 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 Settings
- vLLM
How to use Qwen/Qwen3-VL-235B-A22B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Qwen/Qwen3-VL-235B-A22B-Instruct" # 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-VL-235B-A22B-Instruct", "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/Qwen/Qwen3-VL-235B-A22B-Instruct
- SGLang
How to use Qwen/Qwen3-VL-235B-A22B-Instruct 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-VL-235B-A22B-Instruct" \ --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-VL-235B-A22B-Instruct", "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 "Qwen/Qwen3-VL-235B-A22B-Instruct" \ --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-VL-235B-A22B-Instruct", "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 Qwen/Qwen3-VL-235B-A22B-Instruct with Docker Model Runner:
docker model run hf.co/Qwen/Qwen3-VL-235B-A22B-Instruct
Listed on OpenModelMap
#25 opened 8 days ago
by
duola15
Listed on OpenModelMap
#24 opened 21 days ago
by
duola15
Qwen3-VL-235B-A22B-Instruct-AWQ returns chinese characters
#21 opened 6 months ago
by
ayushaihi
new pull
#20 opened 6 months ago
by
tangyu12143
get
#19 opened 6 months ago
by
tangyu12143
Add Artificial Analysis evaluations for qwen3-vl-235b-a22b-instruct
#18 opened 7 months ago
by
mackenzietechdocs
Add pipeline tag
#17 opened 8 months ago
by
multimodalart
Can we please add TGI support
π 1
#16 opened 8 months ago
by
regnum93
Why does it ramble?
#15 opened 8 months ago
by
Lockout
Request to Add AWQ Quantization Model
β€οΈ 1
1
#13 opened 9 months ago
by
wunu
Is the mlx version on the road?
ππ 3
2
#11 opened 10 months ago
by
ianthereal-z
Output messy code with demo code.
2
#10 opened 10 months ago
by
kk3dmax
No output_router_logits / load_balancing_loss_func for Qwen3VLMoE?
3
#9 opened 10 months ago
by
plcedoz38
Are you guys not going to release base models anymore?
π 2
#8 opened 10 months ago
by
Aly87
π Best Practices for Evaluating the Qwen3-VL Model
#7 opened 10 months ago
by
Yunxz
π₯π₯π₯δΈζζ΅θ―θ§ι’οΌ
π 1
#6 opened 10 months ago
by
leo009
Adding `transformers` library tag
#4 opened 10 months ago
by
ariG23498
Will smaller models like 7B be released?
β 34
4
#3 opened 10 months ago
by
CelYuan
π Qwen3-VL Fine-tuning support. (transformers & Megatron)
#2 opened 10 months ago
by
study-hjt
Is the Qwen3-VL Vision Encoder Based on siglip2-so400m-patch16?
4
#1 opened 10 months ago
by
JosephusCheung