Qwen News 07/20/2026 AI Rating: Medium

Alibaba's Tongyi Lab Unveils "Qwen-Audio-3.0-TTS" — Claims Leaderboard Top Spot at a Third of ElevenLabs' Price

#Qwen#Alibaba#TTS#Text-to-Speech

On July 20, 2026, Alibaba’s Tongyi Lab unveiled a new text-to-speech (TTS) model called “Qwen-Audio-3.0-TTS.” Rather than shipping as open weights, it’s offered as a hosted API through Alibaba Cloud Model Studio in two tiers — “Flash” and “Plus” — covering 16 languages. The Plus tier reportedly took the top spot on Artificial Analysis’s text-to-speech leaderboard, and pricing is set at roughly a third of what competitors like ElevenLabs charge.

Details

  • Two tiers: “Flash” (model ID qwen-audio-3.0-tts-flash) is tuned for real-time conversation with first-packet latency in the 300ms range, while “Plus” (qwen-audio-3.0-tts-plus) prioritizes naturalness and timbre fidelity over raw speed
  • Pricing: $27.59 per 1 million characters — roughly a third of what rivals such as ElevenLabs and MiniMax charge
  • Language support: 16 languages including Arabic, Chinese, English, French, German, Indonesian, Italian, Japanese, Korean, Malay, Portuguese, Russian, Spanish, Tagalog, Thai, and Vietnamese, plus 20 Chinese dialect regions
  • Benchmark results: Plus ranks #1 on the Artificial Analysis Text-to-Speech leaderboard with an Elo rating of roughly 1,236, and posts the best word/character error rate (WER/CER) in 10 of the 16 languages. Average WER/CER is 3.87 for Flash and 3.96 for Plus
  • Speaker similarity: Plus averages 82.75 and Flash 80.44 across all languages, a claim of strong voice fidelity
  • Throughput trade-off: Plus generates only around 16 characters per second, notably slower than competitors like Simba 3.2 (30.2 chars/sec), Gemini 3.1 Flash TTS (27 chars/sec), and Sonic 3.5 (120 chars/sec)
  • Delivery model: API-only, not open-weight. Available via bidirectional WebSocket streaming from Singapore and Beijing regions

How to try it

  • Accessible via the DashScope SDK through Alibaba Cloud Model Studio, with sample code provided in Python, Java, Go, C#, PHP, and Node.js
  • No open-weight release has been announced; usage currently requires going through the hosted API