Qwen3.5 397B A17B

latest

Model IDQwen/Qwen3.5-397B-A17B

Qwen3.5-397B-A17B is Alibaba's flagship open-source model — the first in the Qwen3.5 series (released February 16, 2026) and the most capable open-weight model in the family. It is a native multimodal model trained from scratch on trillions of text, image, and video tokens using early fusion across 201 languages. With 397B total parameters and 17B active per token, it outperforms all Qwen3-VL models on vision tasks while matching or exceeding text-only frontiers. The hosted version is called Qwen3.5-Plus.

256K Tokens (up to 1M via Qwen3.5-Plus API) ContextFast InferenceCodingFunction CallingMultilingualVision Ready

Save 20%

$0.75$0.60

/ 1M input tokens

$4.5$3.6

/ 1M output tokens

Get API Key

Request (Non streaming)

Open in Playground

from openai import OpenAI

# Initialize the OpenAI client with Qubrid base URL
client = OpenAI(
    base_url="https://qubrid.com/v1",
    api_key="QUBRID_API_KEY",
)

response = client.chat.completions.create(
    model="Qwen/Qwen3.5-397B-A17B",
    messages=[
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What is in this image? Describe the main elements."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
            }
          }
        ]
      }
    ],
    max_tokens=16384,
    temperature=0.6,
    top_p=0.95,
    stream=False,
    extra_body={
        "enable_thinking": False,
    }
)

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

Example response

The image shows a clear visual scene with distinct subjects, background context, and balanced composition. Notable elements include primary objects, spatial layout, color and lighting, and any readable text or symbols that support a concise description.

Request (Non streaming)

Open in Playground

from openai import OpenAI

# Initialize the OpenAI client with Qubrid base URL
client = OpenAI(
    base_url="https://qubrid.com/v1",
    api_key="QUBRID_API_KEY",
)

response = client.chat.completions.create(
    model="Qwen/Qwen3.5-397B-A17B",
    messages=[
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What is in this image? Describe the main elements."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
            }
          }
        ]
      }
    ],
    max_tokens=16384,
    temperature=0.6,
    top_p=0.95,
    stream=False,
    extra_body={
        "enable_thinking": False,
    }
)

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

Example response

The image shows a clear visual scene with distinct subjects, background context, and balanced composition. Notable elements include primary objects, spatial layout, color and lighting, and any readable text or symbols that support a concise description.

Multimodal messages with image_url • Streaming and tool calls supported Open in Playground for streaming, files, and all parameters.

Open in Playground

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The image shows a clear visual scene with distinct subjects, background context, and balanced composition. Notable elements include primary objects, spatial layout, color and lighting, and any readable text or symbols that support a concise description.