Qwen3-TTS-Instruct-Flash

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Overview

Qwen3-TTS-Flash model is Tongyi's latest real-time speech synthesis model. The Instruct model processes the synthesis effect through natural language, ensuring highly appropriate emotional and expressive speech in different contexts. Currently, it supports 25 timbres for both Chinese and English Instruct adjustments. This model is a snapshot version from January 26, 2026.

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
$0.115Per 10,000 characters

Rate Limits

RPMRequests Per Minute
180

API Reference

Call API

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import os
import dashscope

dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

text = "Dear listeners, hello everyone. Welcome to the evening news."

response = dashscope.MultiModalConversation.call(
    model="qwen3-tts-instruct-flash-2026-01-26",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    text=text,
    voice="Cherry",
    instructions='The speaking speed is fast and there is a distinct upward inflection, which is suitable for introducing fashionable products.',
    optimize_instructions=True,
    stream=False
)
print(response)