Alibaba
Qwen3 TTS Flash
Alibaba’s low-latency TTS tier for high-volume, real-time voice pipelines.
Intelligenza
88.1 #29
AAQI 88.0
Velocità Uscita
230 t/s
ITL 4.3 ms/tok
Prezzo combinato (3:1)
$0.006 /1M
Input $0.005/M · Output $0.01/M
Contesto
32K
≈ 80 pagine A4 · output max 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Qwen3 TTS Flash
Claude Mythos Preview (#1)
Average (68)
Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.
Punti di forza e compromessi
Dove vince
- ~80ms TTFT for live conversational turns
- Lowest cost-per-character in the premium tier
- Strong APAC language quality
A cosa fare attenzione
- Thinner emotional range than Eleven v3
- Proprietary — no self-hosting
- Fewer voice-customization controls
Casi d'uso killer
High-volume voice bots
Cheap real-time speech at call-center scale.
APAC voice products
Native-quality zh/ja/ko synthesis.
Notification TTS
Mass short-message voice generation.
Quickstart per sviluppatori e API
Imposta prima
DASHSCOPE_API_KEY — ottieni una chiave APIcurl https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "qwen3-tts-flash",
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
api_key=os.environ["DASHSCOPE_API_KEY"],
)
resp = client.chat.completions.create(
model="qwen3-tts-flash",
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(resp.choices[0].message.content)const res = await fetch("https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.DASHSCOPE_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "qwen3-tts-flash",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);Risorse e link ufficiali
Deployment API
Confronta host e latenza
Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Punteggi per Fonte
Punteggi per Categoria
Risultati dei Benchmark
Specifiche live e architettura
Sotto il cofano
Qwen3 TTS Flash — low-latency speech tier
- Flash serving tier — ~80ms streaming TTFT
- 230× realtime-factor synthesis
- Multi-language coverage tuned for APAC locales
- Cheapest premium TTS per million characters
Data di Rilascio
2 ott 2026
Architettura
Qwen3 TTS Flash — low-latency speech tier
Parametri
Not disclosed
Licenza
Proprietary
Finestra di Contesto
32,000 tokens
Output max
8,192 tokens
Modalità
text + audio
Prezzi cache
lettura $0.002 · scrittura $0.006 /1M
Ragionamento
—
Prezzo Ingresso
$0.005/M
Prezzo Uscita
$0.01/M
Velocità Uscita
230 t/s
Tempo al Primo Token
—
Dati aggiornati
22 ott 2026
Stima bolletta mensile
Spesa mensile stimata
$0.00
Calcolo risparmio vs GPT-4o…
Cita e incorpora
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026qwen3ttsflash,
title = {Benchmark Analysis and Intelligence Evaluation of Qwen3 TTS Flash},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/qwen3-tts-flash}
}Incorpora il badge del punteggio
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Modelli alternativi
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