OpenAI: Whisper Large V3 Turbo

1 provider live

openai/whisper-large-v3-turbo

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1 live provider

Whisper Large V3 Turbo is an optimized version of OpenAI's Whisper Large V3 speech recognition model, designed for speed and cost efficiency. It supports transcription across 99+ languages with a 12% word error rate, and accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg. Achieves real-time speed factors up to 216x, making it well-suited for latency-sensitive and high-throughput transcription workloads.

Input: $3.33; per million seconds of audio

Providers

Ranked by price and speed. Requests go to the best healthy provider, then fail over down the list.

#	Provider	Input
1	DeepInfraNon-EU Data policy not declared	$3.33/M seconds

Want to serve this model?Become a provider

Price history

No price changes since Oct 23, 2026.

DeepInfra$3.33/M seconds

Questions

How much does OpenAI: Whisper Large V3 Turbo cost?

OpenAI: Whisper Large V3 Turbo costs $3.33 per million seconds of audio at DeepInfra, the provider requests go to first.

Do providers train on my prompts?

Each provider declares it, and the table above shows every declaration. You can limit a request to providers that keep nothing, or to providers in the EU.

Can I serve OpenAI: Whisper Large V3 Turbo myself?

Yes. Apply as a provider, add your endpoint and list this model at your price. It goes live once the automated check passes.

Similar models

OpenAI: Whisper Large V3openai/whisper-large-v3

$7.50 per million seconds of audio. 2 providers.

Call it

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.llm.buzz/api/v1",
    api_key=os.environ["LLM_BUZZ_KEY"],
)
with open("call.mp3", "rb") as audio:
    transcript = client.audio.transcriptions.create(
        model="openai/whisper-large-v3-turbo",
        file=audio,
    )

import fs from "node:fs";
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.llm.buzz/api/v1",
  apiKey: process.env.LLM_BUZZ_KEY,
});
const transcript = await client.audio.transcriptions.create({
  model: "openai/whisper-large-v3-turbo",
  file: fs.createReadStream("call.mp3"),
});

curl https://api.llm.buzz/api/v1/audio/transcriptions \
  -H "Authorization: Bearer $LLM_BUZZ_KEY" \
  -F model=openai/whisper-large-v3-turbo \
  -F file=@call.mp3

Endpoints

POST /api/v1/audio/transcriptions

Authentication

Send your llm.buzz key as a Bearer token: Authorization: Bearer $LLM_BUZZ_KEY. Create keys in the console. The same key calls every model; each request pays the price of the provider that answered it.

More in Authentication and the API reference.

Call OpenAI: Whisper Large V3 Turbo with one keyEach request pays the price of the provider that answered it.

Get API key