Eleven Multilingual v3
ElevenLabs’ multilingual TTS flagship — 70+ languages, emotional audio tags and ultra-low latency.
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Radar-Achsen sind aus Kategorie-Scores approximiert, wo direkte Benchmark-Messungen fehlen — siehe Methodik.
Stärken & Trade-offs
Wo das Modell gewinnt
- Best-in-class emotional range and prosody
- Ultra-low latency for real-time voice agents
- Broadcast-quality multi-speaker scenes
- 70+ languages on one voice
Worauf achten
- Premium per-character pricing
- Audio tags need prompt-side tuning
- Closed API — no self-hosting
Killer-Anwendungsfälle
Developer-Quickstart & API
ELEVENLABS_API_KEY — API-Schlüssel holencurl -X POST "https://api.elevenlabs.io/v1/text-to-speech/VOICE_ID" \
-H "xi-api-key: $ELEVENLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text": "Welcome to the future of voice agents.", "model_id": "eleven_v3"}' \
--output speech.mp3import os, requests
resp = requests.post(
"https://api.elevenlabs.io/v1/text-to-speech/VOICE_ID",
headers={"xi-api-key": os.environ["ELEVENLABS_API_KEY"]},
json={"text": "Welcome to the future of voice agents.", "model_id": "eleven_v3"},
)
open("speech.mp3", "wb").write(resp.content)const res = await fetch("https://api.elevenlabs.io/v1/text-to-speech/VOICE_ID", {
method: "POST",
headers: { "xi-api-key": process.env.ELEVENLABS_API_KEY, "Content-Type": "application/json" },
body: JSON.stringify({ text: "Welcome to the future of voice agents.", model_id: "eleven_v3" }),
});
await fs.promises.writeFile("speech.mp3", Buffer.from(await res.arrayBuffer()));Text-to-speech — replace VOICE_ID with a voice from your library; returns an audio stream.
Offizielle Ressourcen & Links
Hosts & Latenz vergleichen
Durchsatz, TTFT und Cache-Preise bei Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock und Azure.
Ergebnisse nach Quelle
Kategorie-Punkte
Benchmark-Ergebnisse
Direkte Live-Duelle
Live-Spezifikationen & Architektur
- 70+ languages with cross-lingual voice transfer
- Inline audio tags — [laughs], [whispers], dramatic pauses
- Sub-80ms streaming TTFT for live agents
- Studio-grade multi-speaker dialogue mode
Geschätzte Monatsrechnung
Zitieren & Einbetten
Loading badge markdown...@misc{llmpodium2026elevenv3,
title = {Benchmark Analysis and Intelligence Evaluation of Eleven Multilingual v3},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/eleven-v3}
}Score-Badge einbetten
Fügen Sie Ihrem GitHub- oder Hugging-Face-README ein Live-Podium-Score-Badge hinzu — es verlinkt auf das Live-Ranking.
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