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Qwen-Audio-3.1-TTS-Next

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Overview

Qwen-Audio-3.1-TTS-Next is an AudioGen model designed for unified audio generation. Going beyond conventional TTS systems that focus solely on speech synthesis, it can generate complete audio content in a single pass from inputs such as text, timestamps, and reference audio, seamlessly combining speech, sound effects, ambient sounds, background music, and more. The model supports a wide range of tasks, including multilingual TTS, single-speaker speech, multi-speaker dialogue, podcasts, cinematic soundscapes, music generation, ambient audio, and sound effects. Its key strengths include more natural and expressive speech, consistent voice identity, flexible timing control, and high-quality music and soundscape generation. These capabilities make it well suited for content creation, short-form video, podcasts, film and television production, game audio, and other professional audio creation scenarios.

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

  • Input
    $0.93Per 1M tokens
  • Output
    $1.87Per 1M tokens

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://ap-southeast-1.maas.qwencloudapi.com/api-ws/v1/inference'

model = "qwen-audio-3.1-tts-next"

#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)