Instructions to use Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound with Transformers:

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

pipe = pipeline("text-generation", model="Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound")
model = AutoModelForCausalLM.from_pretrained("Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound", device_map="auto")
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 Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound

SGLang

How to use Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound 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 "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound" \
    --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": "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound",
		"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 "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound" \
        --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": "Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound with Docker Model Runner:
```
docker model run hf.co/Intel/Qwen3-Next-80B-A3B-Thinking-int4-mixed-AutoRound
```

No longer works with vllm

by bgreene010 - opened Nov 10, 2025

Discussion

bgreene010

Nov 10, 2025

FYI, after an update in vllm, it crashes with this model, with the following error.

RuntimeError: No Qwen3Next layer found in the model.layers

This is the first commit in vllm where this happens:

commit e50c45467215f96068d95736b08d8a25f624e67d
Author: Ilya Markov <markovilya197@gmail.com>
Date:   Wed Nov 5 16:22:17 2025 +0100

    [BugFix] Support EP/DP + EPLB with MTP (#25311)

    Signed-off-by: ilmarkov <markovilya197@gmail.com>
    Signed-off-by: Sage Moore <sage@neuralmagic.com>
    Co-authored-by: Sage Moore <sage@neuralmagic.com>
    Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com>
    Co-authored-by: Lucas Wilkinson <LucasWilkinson@users.noreply.github.com>

nephepritou

Nov 18, 2025

https://github.com/vllm-project/vllm/pull/28960 - you can fix it in venv or in docker image manually. Very simple.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment