Alibaba
Qwen3 TTS Flash
Alibaba’s low-latency TTS tier for high-volume, real-time voice pipelines.
Inteligensi
88.1 #29
AAQI 88.0
Kecepatan output
230 t/s
ITL 4.3 ms/tok
Harga gabungan (3:1)
$0.006 /1M
Input $0.005/M · Output $0.01/M
Konteks
32K
≈ 80 halaman A4 · output maks 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Qwen3 TTS Flash
Claude Mythos Preview (#1)
Average (68)
Sumbu radar diaproksimasi dari skor kategori jika pengukuran benchmark langsung tidak tersedia — lihat Metodologi.
Kelebihan & Trade-off
Di mana ia menang
- ~80ms TTFT for live conversational turns
- Lowest cost-per-character in the premium tier
- Strong APAC language quality
Hal yang perlu diperhatikan
- Thinner emotional range than Eleven v3
- Proprietary — no self-hosting
- Fewer voice-customization controls
Kasus Penggunaan 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 Developer & API
Atur
DASHSCOPE_API_KEY dulu — dapatkan kunci 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);Sumber Daya & Tautan Resmi
Deployment API
Bandingkan host & latensi
Throughput, TTFT, dan harga cache di Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock, dan Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Skor per sumber
Skor per kategori
Hasil benchmark
Spesifikasi Live & Arsitektur
Di balik kap
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
Tanggal rilis
2 Okt 2026
Arsitektur
Qwen3 TTS Flash — low-latency speech tier
Parameter
Not disclosed
Lisensi
Proprietary
Jendela konteks
32,000 tokens
Output maks
8,192 tokens
Modalitas
text + audio
Harga cache
baca $0.002 · tulis $0.006 /1M
Penalaran
—
Harga input
$0.005/M
Harga output
$0.01/M
Kecepatan output
230 t/s
Waktu ke token pertama
—
Data diperbarui
22 Okt 2026
Estimasi tagihan bulanan
Estimasi pengeluaran bulanan
$0.00
Menghitung penghematan vs GPT-4o…
Kutip & sematkan
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}
}Sematkan Lencana Skor
Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.
Pratinjau
Markdown
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Model Alternatif
Alternatif terdekat untuk Qwen3 TTS Flash berdasarkan kemampuan, harga, dan skor benchmark.