Qwen3-Omni-Flash

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Overview

Qwen3-Omni-Flash multimodal large-scale model, based on the Thinker–Talker Mixed Expert (MoE) architecture, supports efficient understanding and speech generation of text, images, audio, and video. It can interact with text in 119 languages and speech in 20 languages, generating human-like speech for precise cross-lingual communication. The model boasts powerful command-following and system prompt customization capabilities, flexibly adapting to conversational styles and character settings. It is widely used in scenarios such as text creation, voice assistants, and multimedia analysis, providing a natural and smooth multimodal interaction experience.

Input

TextImageAudioVideo

Output

TextAudio

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: Text
$0.43Per 1M tokens
Input: Audio
$3.81Per 1M tokens
Input: Vision
$0.78Per 1M tokens
Output: Text (When input contains only text)
$1.66Per 1M tokens
Output: Text (When input contains images/audio/video)
$3.06Per 1M tokens
Output: Text&Audio (Output text is not charged)
$15.11Per 1M tokens
Input: Text(Thinking)
$0.43Per 1M tokens
Input: Audio(Thinking)
$3.81Per 1M tokens
Input: Vision(Thinking)
$0.78Per 1M tokens
Output: Text (in thinking mode, when input contains only text)
$1.66Per 1M tokens
Output: Text (in thinking mode, when the input contains images/audio/video)
$3.06Per 1M tokens

Rate Limits

TPMTokens Per Minute
100K
RPMRequests Per Minute
60

API Reference

Call API

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import os
from openai import OpenAI

client = OpenAI(
    # The API keys for the Singapore and Beijing regions are different. To obtain an API key, see: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen3-omni-flash",
    messages=[{"role": "user", "content": "Who are you"}],
    # Set the modality for the output data. The following modalities are supported: ["text","audio"]、["text"]
    modalities=["text", "audio"],
    audio={"voice": "Ethan", "format": "wav"},
    # The stream parameter must be set to True. Otherwise, an error is reported
    stream=True,
    stream_options={"include_usage": True},
)

for chunk in completion:
    if chunk.choices:
        print(chunk.choices[0].delta)
    else:
        print(chunk.usage)