Qwen3-TTS-VD-Realtime

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Overview

Qwen 3-TTS-VD model is Tongyi's latest real-time speech synthesis model. It can perform high-fidelity real-time speech synthesis on the voices designed by the qwen3-voice-design service, and supports speech output in 11 languages ​​using the same voice. This model has been trained on massive amounts of data, and the synthesized audio can adaptively adjust its tone according to the text, demonstrating good processing capabilities for complex text synthesis. This model is a snapshot version from December 16, 2025.

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
    $0.13Per 10,000 characters

Rate Limits

  • RPMRequests Per Minute
    180

API Reference

Call API
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import os
import base64
import threading
import time
import dashscope
from dashscope.audio.qwen_tts_realtime import *

qwen_tts_realtime: QwenTtsRealtime = None
text_to_synthesize = [
    'What's the weather like today?'
]

DO_VIDEO_TEST = False

def init_dashscope_api_key():
    """
        Set your DashScope API-key. More information:
        https://github.com/aliyun/alibabacloud-bailian-speech-demo/blob/master/PREREQUISITES.md
    """
    if 'DASHSCOPE_API_KEY' in os.environ:
        dashscope.api_key = os.environ[
            'DASHSCOPE_API_KEY']  # load API-key from environment variable DASHSCOPE_API_KEY
    else:
        dashscope.api_key = 'your-dashscope-api-key'  # set API-key manually



class MyCallback(QwenTtsRealtimeCallback):
    def __init__(self):
        self.complete_event = threading.Event()
        self.file = open('result_24k.pcm', 'wb')

    def on_open(self) -> None:
        print('connection opened, init player')

    def on_close(self, close_status_code, close_msg) -> None:
        self.file.close()
        print('connection closed with code: {}, msg: {}, destroy player'.format(close_status_code, close_msg))

    def on_event(self, response: str) -> None:
        try:
            global qwen_tts_realtime
            type = response['type']
            if 'session.created' == type:
                print('start session: {}'.format(response['session']['id']))
            if 'response.audio.delta' == type:
                recv_audio_b64 = response['delta']
                self.file.write(base64.b64decode(recv_audio_b64))
            if 'response.done' == type:
                print(f'response {qwen_tts_realtime.get_last_response_id()} done')
            if 'session.finished' == type:
                print('session finished')
                self.complete_event.set()
        except Exception as e:
            print('[Error] {}'.format(e))
            return

    def wait_for_finished(self):
        self.complete_event.wait()


if __name__  == '__main__':
    init_dashscope_api_key()

    print('Initializing ...')

    callback = MyCallback()

    qwen_tts_realtime = QwenTtsRealtime(
        model='qwen3-tts-vd-realtime-2025-12-16',
        callback=callback, 
        url='wss://dashscope-intl.aliyuncs.com/api-ws/v1/realtime'
        )

    qwen_tts_realtime.connect()
    qwen_tts_realtime.update_session(
        # Replace the following voice
        voice = 'your_design_voice',
        response_format = AudioFormat.PCM_24000HZ_MONO_16BIT,
        mode = 'server_commit'        
    )
    for text_chunk in text_to_synthesize:
        print(f'send texd: {text_chunk}')
        qwen_tts_realtime.append_text(text_chunk)
        time.sleep(0.1)
    qwen_tts_realtime.finish()
    callback.wait_for_finished()
    print('[Metric] session: {}, first audio delay: {}'.format(
                    qwen_tts_realtime.get_session_id(), 
                    qwen_tts_realtime.get_first_audio_delay(),
                    ))