Qwen-Audio-3.1-TTS

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Overview

Qwen-Audio-3.1-TTS-Flash is a high-performance text-to-speech large model designed for real-time interactive scenarios, supporting multiple languages and dialects. The model features free-style instruction-following capability and fine-grained tag-based control, enabling flexible manipulation of emotion, tone, persona, speaking rate, volume, and other expressive attributes. In voice cloning scenarios, the model demonstrates enhanced robustness under complex acoustic conditions such as noise and reverberation, with improved audio quality, clarity, and overall expressiveness. The Flash version focuses on optimizing the real-time synthesis experience, making it well suited for low-latency interactive use cases including voice assistants, live conversations, and intelligent customer service.

Input

TextAudio

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
6K

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-3.1-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)