qwen/qwen3.8-27b

The larger reasoning-capable multimodal chat model. It accepts text, images, and video with a 200K-token context window. Default and only method: free-form chat (no method or method_params). It accepts up to 64 image_url parts or one video_url. Tune video sampling with video_fps, video_max_frames, and video_resolution at the top level. See Video Inputs. The deployed weights are Inferact/Qwen3.8-27B-NVFP4, based on upstream Qwen/Qwen3.8-27B.

Output by method

Method	Payload	Envelope
chat (default)	The model’s reply, verbatim	None, in either mode

A chat VLM is pass-through. Text mode returns the reply with no wrapper, even with several images: the model reads them together and produces one reply. JSON mode returns the model’s own JSON, with no data envelope. See Methods & Response Format. It does not accept document_url. A PDF request is a 400 capability error. For PDFs use an OCR model, for example paddleocr/pp-ocrv6.

Request

vlmrun gw chat https://storage.googleapis.com/vlm-data-public-prod/hub/examples/image.caption/car.jpg \
  -p "What is happening in this image?" \
  -m qwen/qwen3.8-27b

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.vlm.run/v1/openai",
    api_key="<VLMRUN_API_KEY>",
)

response = client.chat.completions.create(
    model="qwen/qwen3.8-27b",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What is happening in this image?"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/image.caption/car.jpg"
                    },
                },
            ],
        }
    ],
)

print(response.choices[0].message.content)

curl https://gateway.vlm.run/v1/openai/chat/completions \
  -X POST \
  -H "Authorization: Bearer $VLMRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.8-27b",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "What is happening in this image?" },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/image.caption/car.jpg"
            }
          }
        ]
      }
    ]
  }'

Response

Text mode
JSON mode

A silver sedan is parked on a sunlit street beside a row of trees.

Add response_format={"type":"json_object"} in the body and ask for JSON in the prompt. The reply is the model’s own JSON, with no envelope:

{ "vehicle": "silver sedan", "setting": "sunlit street beside a row of trees" }

For video, pass a video_url part and tune sampling with video_fps / video_max_frames. See Video Inputs.

Overview

Guides

API Reference

Misc

qwen/qwen3.8-27b

Output by method

Request

Response

​Output by method

​Request

​Response

Output by method

Request

Response