New Multimodal

Qwen3.8 27B

Qwen's dense 27B vision-language model for coding, research, and long-horizon agents with controllable thinking and native speculative decoding through MTP

Command to Run on Jetson Model Details

Parameters 27B

Modalities

Text Image Video

Context Length 262K

License Apache 2.0

Precision

Q4_K_M GGUF

Serve the model

Start server

Choose module, then engine and optional parameters on the left, then copy the serve command by clicking the button on the right.

Command

Call the model over Web API

Copy a client command below and paste it into your terminal to make a Web API request to the model you just served.

llama.cpp server (OpenAI-compatible API)

After llama-server is running with --network host, call it from another machine on the LAN (set ${JETSON_HOST} or use the field). Default port is often 8080 unless you set --port.

curl -s http://${JETSON_HOST}:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "my_model",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from openai import OpenAI

client = OpenAI(
    base_url="http://${JETSON_HOST}:8080/v1",
    api_key="not-needed",  # vLLM / llama.cpp typically do not enforce a key
)

completion = client.chat.completions.create(
    model="my_model",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(completion.choices[0].message.content)

Model Details

View on HuggingFace

Qwen3.8 27B is Qwen’s dense, open-weight vision-language model for coding, professional work, research, and long-horizon agentic tasks. It brings the strongest generation of Qwen open models to a deployment-friendly size, with better planning and stronger handling of tool and environment feedback for more reliable multi-step task completion.

Thinking is enabled by default and can be disabled per request. Reasoning depth is adjustable with xhigh, medium, and low effort levels, while preserved thinking carries reasoning context across turns. The model also supports a native 262K context window and is trained with multi-step MTP, which the Jetson commands enable for faster generation.

Modalities

Input: Text, image, and video

Output: Text