Whisper large-v3-turbo
Fast speech-to-text in 99 languages, Sinhala and Tamil among them.
About Whisper large-v3-turbo
Whisper large-v3-turbo turns speech into text in 99 languages. It is a slimmed-down Whisper large-v3: OpenAI cut its decoder from 32 layers to 4 and retrained it, making it much faster for accuracy roughly on par with the earlier large-v2. It is the default model in OpenAI’s open-source Whisper today.
Use it for meeting and call transcripts, subtitles and voice notes. Like every Whisper, it can occasionally write words that were never said, especially over silence or noise, so keep a person checking transcripts that matter.
Where it’s strong
Meeting and call transcripts.
Subtitles and captions.
Voice notes and voice input in apps.
Where to be careful
Not built for translating speech into English — OpenAI left translation out of its training.
Can invent text that is not in the audio, and accuracy drops on strong accents and less common languages.
Price
Every rate is published and stays the same from one request to the next. See every model.
Specs
whisper-large-v3-turboCall it
Use the OpenAI SDK you already have — point it at Roar AI and name the model. Read the docs.
from openai import OpenAI
client = OpenAI(base_url="https://api.roar-ai.com/v1", api_key="roar_live_…")
text = client.audio.transcriptions.create(
model="whisper-large-v3-turbo",
file=open("call-recording.mp3", "rb"),
)Questions
How much does Whisper large-v3-turbo cost?
Price is $14.4444 per 1M audio seconds. The rate is published and does not change from one request to the next.
Can I use Whisper large-v3-turbo alongside other models?
Yes. Every model on Roar AI is on the same API key and the same monthly invoice, so switching from Whisper large-v3-turbo to another model is a change to one word in your code.
Is Whisper large-v3-turbo open source?
Its weights are open under the MIT licence, so you could run it yourself. Through Roar AI you call it like any other model, with no servers to manage.