ElevenLabs
ElevenLabs Scribe v2
ElevenLabs’ second-generation speech-to-text — 90+ languages, speaker diarization and sub-200ms streaming.
Intelligenza
92.5 #10
AAQI 93.0
Velocità Uscita
240 t/s
ITL 4.2 ms/tok
Prezzo combinato (3:1)
$0.01 /1M
Input $0.008/M · Output $0.016/M
Contesto
64K
≈ 160 pagine A4 · output max 8,192
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
ElevenLabs Scribe v2
Claude Mythos Preview (#1)
Average (68)
Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.
Punti di forza e compromessi
Dove vince
- Top-tier WER across 90+ languages
- Realtime partials fast enough for barge-in agents
- Built-in diarization — no extra pipeline
A cosa fare attenzione
- STT only — pair with an LLM and TTS for full loops
- Per-minute pricing adds up on call centers
- No on-prem option
Casi d'uso killer
Voice-agent front end
Streaming transcripts with low-latency turn detection.
Meeting intelligence
Diarized, timestamped records at scale.
Multimedia subtitling
Multi-language caption pipelines.
Quickstart per sviluppatori e API
Imposta prima
ELEVENLABS_API_KEY — ottieni una chiave APIcurl -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": "scribe_v2"}' \
--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": "scribe_v2"},
)
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: "scribe_v2" }),
});
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.
Risorse e link ufficiali
Deployment API
Confronta host e latenza
Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Groq
Cerebras
Together AI
DeepInfra
Fireworks AI
AWS Bedrock
Azure AIPunteggi per Fonte
Punteggi per Categoria
Risultati dei Benchmark
Scontri diretti live
Claude Fable 5-0.9
GPT-Image 2-0.6
Grok Imagine Quality-0.1Specifiche live e architettura
Sotto il cofano
Scribe v2 — streaming speech recognition
- 90+ languages with automatic language ID
- Speaker diarization and word-level timestamps
- Sub-200ms partial transcripts for live agents
- Noise-robust far-field microphone handling
Data di Rilascio
19 ott 2026
Architettura
Scribe v2 — streaming speech recognition
Parametri
Not disclosed
Licenza
Proprietary
Finestra di Contesto
64,000 tokens
Output max
8,192 tokens
Modalità
audio
Prezzi cache
lettura $0.003 · scrittura $0.01 /1M
Ragionamento
—
Prezzo Ingresso
$0.008/M
Prezzo Uscita
$0.016/M
Velocità Uscita
240 t/s
Tempo al Primo Token
—
Dati aggiornati
22 ott 2026
Stima bolletta mensile
Spesa mensile stimata
$0.00
Calcolo risparmio vs GPT-4o…
Cita e incorpora
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026elevenlabsscribev2,
title = {Benchmark Analysis and Intelligence Evaluation of ElevenLabs Scribe v2},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/elevenlabs-scribe-v2}
}Incorpora il badge del punteggio
Aggiungi un badge Podium Score live al tuo README su GitHub o Hugging Face — rimanda alla classifica live.
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