Qwen3-Omni-Flash

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Multimodal

Overview

Multimodal

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

Function Calling

Cache

Structured Outputs

Batches

Web Search

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

  • RPMRequests Per Minute
    60
  • TPMTokens Per Minute
    100K

API Reference

Get API Key
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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)