Qwen3 TTS Flash API

Qwen3-TTS offers 17 voices and supports multiple languages and dialects including Chinese. The system can adapt its tone and smoothly process complex text.

Modalities
TextAudio
Price
$0.013per generation
Voices
17 presets
Released
Jan 5, 2026

Qwen3 TTS Flash overview

Voice
Voice sample

Qwen3 TTS Flash

Generated through AI/ML API on Nov 3, 2026

0:000:08

Generated from the text and settings shown here.

Qwen3 TTS Flash by Alibaba Cloud

It excels in real-time applications, delivering clear, versatile speech suitable for conversational AI, audiobooks, and accessibility tools.

Qwen3 TTS Flash specs

Model ID
alibaba/qwen3-tts-flash
Developer
Alibaba Cloud
Input
Text
Output
Audio
Endpoint
POST https://api.aimlapi.com/v1/tts

Overview

Qwen3-TTS-Flash is an advanced text-to-speech (TTS) engine from Alibaba backed by Qwen, designed for ultra-low latency and high naturalness in speech synthesis. It excels in multilingual and multi-dialect speech generation with state-of-the-art stability and expressiveness, making it ideal for real-time applications such as virtual assistants, gaming NPCs, and interactive voice response systems.

Technical Specifications

  • Model Architecture: Transformer-based encoder-decoder optimized for low-latency inference.
  • Training Data: Extensive datasets covering 119 languages for text and 19 languages for speech understanding.
  • Output Languages: Focus on 10 languages with support for multi-dialect variations.
  • Voices: 17 built-in voice presets allowing effortless switching without retraining.
  • Latency: Single-threaded first-packet latency as low as 97 milliseconds.
  • Deployment: Suitable for deployment in chatbots, IVR systems, gaming, and content creation platforms.

Performance Benchmarks

Qwen3-TTS-Flash demonstrates outstanding performance in text-to-speech synthesis, achieving a Mean Opinion Score (MOS) exceeding 4.3 out of 5, reflecting its natural and clear voice quality. The model delivers synthesis speeds up to five times faster than real-time on standard cloud GPU instances, making it highly suitable for applications requiring low latency. It offers strong prosody control, enabling expressive speech with varied speaking styles and emotional tones. In intelligibility tests, Qwen3-TTS-Flash produces speech with near-perfect word error rates when evaluated through automatic speech recognition systems. The model maintains consistent high-quality output across supported languages, primarily English and Chinese, and robustly handles out-of-vocabulary words and ambiguous pronunciations, ensuring reliable and versatile voice generation.

Key Capabilities

  • High-Fidelity Voice: Generates clear, natural-sounding speech suitable for professional audio content
  • Ultra-Fast Synthesis: Designed for low latency voice generation in streaming or batch modes
  • Multilingual Support: Flexible voice model configuration for multiple languages and dialects
  • Prosody and Style Control: Enables adjustment of pitch, speed, and intonation for expressive speech
  • Lightweight Deployment: Efficient architecture allowing edge and cloud deployment scenarios
  • Open-Source Access: Full Apache 2.0 licensing permits customization and integration

Optimal Use Cases

  • Conversational AI and virtual assistants requiring fast, natural voice responses
  • Audiobook and podcast production with high-quality synthetic narration
  • Accessibility tools including screen readers and voice-enabled devices
  • Multilingual content voice-over and localization
  • Real-time speech interfaces in smart devices, automotive systems, and IoT
  • Interactive voice response (IVR) and customer service bots

Comparison with Other Models

vs Google WaveNet: High synthesis quality with MOS above 4.3 vs very high quality; Qwen3-TTS-Flash provides ultra-low latency near real-time synthesis, while WaveNet has moderate latency; both support prosody control, but WaveNet covers more languages.

vs Amazon Polly Neural: Qwen3-TTS-Flash offers higher quality and advanced prosody control vs Amazon Polly's high but more basic control; Qwen3-TTS-Flash supports edge deployment unlike primarily cloud-based Polly.

vs OpenAI Whisper: Qwen3-TTS-Flash specializes in high-quality TTS with multilingual voice synthesis, whereas Whisper focuses mainly on ASR (speech recognition); Whisper provides limited TTS capabilities and lacks prosody control.

Use cases

  • Conversational AI and virtual assistants requiring fast, natural voice responses
  • Audiobook and podcast production with high-quality synthetic narration
  • Accessibility tools including screen readers and voice-enabled devices
  • Multilingual content voice-over and localization
  • Real-time speech interfaces in smart devices, automotive systems, and IoT
  • Interactive voice response (IVR) and customer service bots

Qwen3 TTS Flash benchmarks by Artificial Analysis

Human-preference results for Qwen3 TTS Flash in speech arena, next to models available on AI/ML API. Data retrieved Nov 3, 2026.

Speech Arena

Elo · text-to-speech arena

AI/ML API price

USD per generation

Models on AI/ML API

Arena results for models you can call with the same API key.

Speech Arena

Listeners hear two clips of the same text and choose the more natural one. Qwen3 TTS Flash ranks #89 of 101.

Qwen3 TTS Flash API pricing

Qwen3 TTS Flash pricing in US dollars
UsagePriceUnit
Speech generation$0.013per generation

Prices from the AI/ML API price list, checked on Nov 4, 2026.

Qwen3 TTS Flash vs other speech models: prices

AI/ML API rates for 5 models, per generation.

AI/ML API prices in USD per generation
ModelPer generation
Qwen3 TTS Flash$0.013
GPT-4o mini TTS$0.001
Inworld TTS-1$0.007
Inworld TTS-1-Max$0.013
MiniMax Speech 2.6 Turbo$0.078

How to use the Qwen3 TTS Flash API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/tts' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "alibaba/qwen3-tts-flash",
  "text": "Your order has shipped. It will arrive on Thursday between nine and eleven in the morning. Reply to this message if you need to change the delivery time."
}'

Related articles

All posts

Qwen3 TTS Flash FAQ

What inputs and outputs does Qwen3 TTS Flash support?

Qwen3 TTS Flash takes text as input and returns audio.

When was Qwen3 TTS Flash released?

Qwen3 TTS Flash became available on January 5, 2026.

How much does Qwen3 TTS Flash cost?

Qwen3 TTS Flash is priced at $0.013 / 1M tokens.

How is Qwen3 TTS Flash billed?

Qwen3 TTS Flash is billed per generation, a fixed charge per output rather than by prompt length.

Who created Qwen3 TTS Flash?

Qwen3 TTS Flash was built by Alibaba Cloud.

How do I call Qwen3 TTS Flash on AI/ML API?

Send a request to https://api.aimlapi.com/v1/tts with alibaba/qwen3-tts-flash as the model id.

Is Qwen3 TTS Flash available through a single API key?

Yes. Qwen3 TTS Flash is served through AI/ML API, so the same key and endpoint format used for other models applies.

What languages does Qwen3 TTS Flash support?

It supports multiple languages and dialects, including Chinese.

How many voice options does Qwen3 TTS Flash provide?

Qwen3 TTS Flash offers 17 voices.

What is the Qwen3 TTS Flash model ID?

Use alibaba/qwen3-tts-flash as the model parameter. Requests go to https://api.aimlapi.com/v1/tts with your AI/ML API key.

Start building with Qwen3 TTS Flash

Qwen3 TTS Flash API

alibaba/qwen3-tts-flash

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/tts' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "alibaba/qwen3-tts-flash",
  "text": "Your order has shipped. It will arrive on Thursday between nine and eleven in the morning. Reply to this message if you need to change the delivery time."
}'