Model Marketplace

Qwen-Audio-TTS

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Overview

Qwen-Audio-3.0-TTS-Flash is a high-performance speech synthesis model , optimized for real-time interactive scenarios. Compared with the previous version, it supports more low-resource languages and Chinese dialects, improves dialect authenticity, and enhances free-style instruction following and fine-grained tag control for more flexible control over emotion, tone, character, speaking rate, volume, and expressive style. It is also more robust under noisy and reverberant acoustic conditions, with improved audio quality, clarity, and overall expressiveness. The Flash version focuses on real-time synthesis, making it suitable for voice assistants, real-time dialogue, intelligent customer service, and other low-latency interactive applications.

Input

Text

Output

Audio

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

  • TTS
    $0.15Per 10,000 characters

Rate Limits

  • RPMRequests Per Minute
    180

API Reference

Call API
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# coding=utf-8

import dashscope
from dashscope.audio.tts_v2 import *

# If the API Key is not configured in the environment variable, your-api-key needs to be replaced with your own API Key
# dashscope.api_key = "your-api-key"

dashscope.base_websocket_api_url='wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference'

model = "qwen-audio-3.0-tts-flash"

#Please enter the correct voice below.
voice = ""

synthesizer = SpeechSynthesizer(model=model, voice=voice)
audio = synthesizer.call("How is the weather today?")

with open('output.mp3', 'wb') as f:
    f.write(audio)