OpenAI Whisper
OpenAI's open-source speech recognition model with industry-standard accuracy for transcription.
Overview
OpenAI’s open-source speech recognition model with industry-standard accuracy for transcription.
OpenAI Whisper: practical overview
OpenAI Whisper is a free, open-source AI model for high-accuracy multilingual transcription and translation. Try it now for word-level timestamps.
OpenAI Whisper is listed in the AI Audio category. This page summarizes the tool's known positioning, core features, pricing model, platform coverage, and common use cases so readers and AI answer engines can understand when the tool is relevant.
Key capabilities
- Open-source
- Multilingual transcription
- Translation
- Word-level timestamps
- High accuracy
Common use cases
- Transcribing podcasts and interviews with high accuracy
- Generating subtitles and captions for videos with timestamps
- Translating foreign language audio into English text
- Building voice-controlled applications and assistants
Tool facts
| Pricing model | Free |
|---|---|
| Platform | Local, API |
| Release date | September 2022 |
| Reported users | 10M+ users |
| Directory rating | 4.7 / 5 |
| Official website | openai.com |
FAQ
What is OpenAI Whisper?
OpenAI Whisper is an open-source automatic speech recognition (ASR) model developed by OpenAI. It transcribes and translates audio into text with high accuracy across multiple languages.
Is OpenAI Whisper free to use?
Yes, OpenAI Whisper is completely free and open-source. You can download and run the model locally without any subscription or API costs.
What languages does Whisper support?
Whisper supports transcription in over 90 languages and can translate many of them into English. It is trained on a massive multilingual dataset for broad language coverage.
Does Whisper provide word-level timestamps?
Yes, Whisper can generate word-level timestamps, making it ideal for subtitling, captioning, and precise audio alignment tasks.
How accurate is OpenAI Whisper compared to other models?
Whisper achieves industry-standard accuracy, often rivaling or surpassing commercial ASR systems, especially in noisy environments and for diverse accents.