Alibaba
Qwen3 TTS Flash
Alibaba’s low-latency TTS tier for high-volume, real-time voice pipelines.
Intelligence
88.1 #29
AAQI 88.0
Output Speed
230 t/s
ITL 4.3 ms/tok
Blended price (3:1)
$0.006 /1M
In $0.005/M · Out $0.01/M
Context
32K
≈ 80 A4 pages · max out 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Qwen3 TTS Flash
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- ~80ms TTFT for live conversational turns
- Lowest cost-per-character in the premium tier
- Strong APAC language quality
Trade-offs to watch
- Thinner emotional range than Eleven v3
- Proprietary — no self-hosting
- Fewer voice-customization controls
Killer Use Cases
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.
Developer Quickstart & API
Set
DASHSCOPE_API_KEY first — get an API keycurl 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);Official Resources & Links
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Scores by Source
Category Scores
Benchmark Results
Head-to-head Live Matchups
Live Specs & Architecture
Under the hood
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
Release date
Oct 2, 2026
Architecture
Qwen3 TTS Flash — low-latency speech tier
Parameters
Not disclosed
License
Proprietary
Context Window
32,000 tokens
Max Output
8,192 tokens
Modalities
text + audio
Cache Pricing
read $0.002 · write $0.006 /1M
Reasoning
—
Input Price
$0.005/M
Output Price
$0.01/M
Output Speed
230 t/s
Time to First Token
—
Data Updated
Oct 22, 2026
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
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}
}Embed Score Badge
Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.
Preview
Markdown
Loading badge snippet...HTML
Loading badge snippet...More from Alibaba
Alternative Models
Closest alternatives to Qwen3 TTS Flash based on capabilities, pricing, and benchmark scores.