Alibaba
Qwen Audio 3.1 TTS+Open
Alibaba’s open-weight TTS — natural prosody, zero-shot voice cloning and 30+ languages.
Intelligence
89.4 #18
AAQI 89.0
Output Speed
140 t/s
ITL 7.1 ms/tok
Blended price (3:1)
$0.013 /1M
In $0.01/M · Out $0.02/M
Context
32K
≈ 80 A4 pages · max out 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Qwen Audio 3.1 TTS+
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
- Best open-weight TTS — rivals commercial tiers
- Voice cloning without per-voice training
- Runs on a single 8GB GPU at Q4
- Cheap hosted API fallback via DashScope
Trade-offs to watch
- Slightly robotic on long emotional passages
- Cloning quality depends on reference audio
- English/Chinese strongest — tail languages vary
Killer Use Cases
Self-hosted voice products
Own TTS for apps needing data control.
Voice cloning pipelines
Zero-shot cloning for personalized agents.
Multilingual IVR
Single checkpoint across 30+ locales.
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": "qwen-audio-tts-plus",
"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="qwen-audio-tts-plus",
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: "qwen-audio-tts-plus",
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
Qwen Audio 3.1 TTS+ — 8B open speech synthesis
- Open weights — self-host the full TTS stack
- Zero-shot voice cloning from ~10s of reference audio
- 30+ languages with code-switch support
- Prosody and style controls via natural-language prompts
Release date
Oct 2, 2026
Architecture
Qwen Audio 3.1 TTS+ — 8B open speech synthesis
Parameters
8B
License
Open Weights
Context Window
32,000 tokens
Max Output
8,192 tokens
Modalities
text + audio
Cache Pricing
read $0.004 · write $0.0125 /1M
Reasoning
—
Input Price
$0.01/M
Output Price
$0.02/M
Output Speed
140 t/s
Time to First Token
—
Data Updated
Oct 22, 2026
Hardware & Local Inference
Data: Convly AI (CC BY 4.0) ↗VRAM (4-bit Q4)
5 GB
Min GPU
RTX 3060 8GB / any 8GB GPU
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
Loading badge markdown...BibTeX
@misc{llmpodium2026qwenaudio31ttsplus,
title = {Benchmark Analysis and Intelligence Evaluation of Qwen Audio 3.1 TTS+},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/qwen-audio-3-1-tts-plus}
}Embed Score Badge
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