Mistral
Voxtral 3 TTS
Mistral’s speech-synthesis Voxtral tier — expressive multilingual TTS in the Mistral stack.
Inteligensi
90.2 #16
AAQI 90.0
Kecepatan output
165 t/s
ITL 6.1 ms/tok
Harga gabungan (3:1)
$0.019 /1M
Input $0.015/M · Output $0.03/M
Konteks
32K
≈ 80 halaman A4 · output maks 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Voxtral 3 TTS
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
- Top EU-language prosody
- One vendor for LLM + TTS + STT
- Competitive latency for conversational use
Hal yang perlu diperhatikan
- English voices trail Eleven v3 on emotion
- Smaller voice library than ElevenLabs
- Closed weights
Kasus Penggunaan Killer
European voice products
Native-quality fr/de/es/it synthesis.
Mistral-native agents
Voice loops inside the Mistral stack.
Accessibility readouts
Natural long-form reading for apps.
Quickstart Developer & API
Atur
MISTRAL_API_KEY dulu — dapatkan kunci APIcurl https://api.mistral.ai/v1/chat/completions \
-H "Authorization: Bearer $MISTRAL_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "voxtral-3-tts",
"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://api.mistral.ai/v1",
api_key=os.environ["MISTRAL_API_KEY"],
)
resp = client.chat.completions.create(
model="voxtral-3-tts",
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://api.mistral.ai/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.MISTRAL_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "voxtral-3-tts",
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
Duel Head-to-head Live
Spesifikasi Live & Arsitektur
Di balik kap
Voxtral 3 TTS — Mistral speech synthesis
- Shares the Voxtral audio encoder lineage
- Expressive multilingual voices with style prompts
- Native EU-language coverage (fr/de/es/it/pt)
- Integrates with Mistral chat and agents
Tanggal rilis
9 Okt 2026
Arsitektur
Voxtral 3 TTS — Mistral speech synthesis
Parameter
Not disclosed
Lisensi
Proprietary
Jendela konteks
32,000 tokens
Output maks
8,192 tokens
Modalitas
text + audio
Harga cache
baca $0.005 · tulis $0.019 /1M
Penalaran
—
Harga input
$0.015/M
Harga output
$0.03/M
Kecepatan output
165 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{llmpodium2026voxtral3tts,
title = {Benchmark Analysis and Intelligence Evaluation of Voxtral 3 TTS},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/voxtral-3-tts}
}Sematkan Lencana Skor
Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.
Pratinjau
Markdown
Loading badge snippet...HTML
Loading badge snippet...Lainnya dari Mistral
Model Alternatif
Alternatif terdekat untuk Voxtral 3 TTS berdasarkan kemampuan, harga, dan skor benchmark.