Model Marketplace

Qwen3.8-Omni-Flash

Copy success!
Add to Compare

Overview

Qwen’s next-generation native omni-modal model supports context lengths of up to 1M tokens and natively accepts text, image, audio, and video inputs. Built on the Qwen3.8-Flash-Next architecture, it is designed for agentic capabilities in real-world productivity scenarios. In addition to coding, knowledge work, GUI interaction, and other agentic tasks, it delivers significant performance gains in workflows that require integrated processing of text, images, audio, and video, including video editing, music video creation, film and video production and narration, multimedia summarization, and audio-video dialogue. It supports two-channel and four-channel spatial audio understanding and is compatible with both the DashScope and OpenAI protocols. We recommend installing the companion Qwen-MM-Plugins to help agent frameworks access its native multimodal capabilities.

Input

TextImageAudioVideo

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Input
    $0.15Per 1M tokens
  • Output
    $0.47Per 1M tokens
  • Input(Implicit Cache)
    $0.016Per 1M tokens

Rate Limits & Context

  • Max Input
    991K
  • Max Output
    131K
  • Max Input (Thinking)
    983K
  • Max Output (Thinking)
    131K
  • Context
    1M
  • Max Reasoning
    262K
  • TPMTokens Per Minute
    2M
  • RPMRequests Per Minute
    30K

Built-in Tools

web_searchResponses API

API Reference

Call API
Copy success!
1234567891011121314151617181920212223242526272829
# Install dependencies: pip install -U openai
# Set DASHSCOPE_API_KEY for the target region before running.
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["DASHSCOPE_API_KEY"],
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen3.8-omni-flash",
    messages=[{"role": "user", "content": "Who are you?"}],
    # Qwen3.8-Omni-Flash supports text output only. Do not set audio.
    modalities=["text"],
    stream=True,
    stream_options={"include_usage": True},
)

for chunk in completion:
    if chunk.choices:
        content = chunk.choices[0].delta.content
        if content:
            print(content, end="", flush=True)
    elif chunk.usage:
        print()
        print("Usage:", chunk.usage)
print()