Whisper
OpenAIAudio & SpeechOpen SourceOpen-source speech recognition model trained on 680,000 hours of multilingual audio. Capable of transcription and translation across 99 languages.
Abilities
Use Cases
Available in Tools
Availability
How to Use
Pros
- Fully open source with MIT license — complete freedom to use, modify, and distribute
- Supports 99 languages with automatic language detection
- Multiple model sizes (tiny 39M to large 1.5B) — trade accuracy for speed as needed
- Can run fully offline on local hardware — no data leaves your machine
- Whisper.cpp port enables real-time transcription on CPU-only devices
- Free to self-host — zero marginal cost per minute of audio processed
Cons
- Large-v3 model requires ~10GB VRAM — not practical on low-end hardware
- Real-time transcription needs significant optimization (batching, VAD, streaming)
- Struggles with heavy accents, fast speech, and domain-specific jargon
- No built-in speaker diarization — cannot distinguish between different speakers
- Can hallucinate repetitive text on silent or noisy audio segments
What to Use It For
Perfect For
Supports 99 languages with automatic detection — process multilingual audio without manual configuration
MIT license and local deployment mean no data leaves your machine — ideal for sensitive audio
Handles long-form conversational audio well with good punctuation and formatting
Good For
Built-in timestamp support produces timed segments ready for SRT/VTT subtitle formats
Smaller model variants (tiny, base) provide fast enough inference for near-real-time command detection
Not Recommended
Out-of-the-box latency is too high — needs VAD, streaming, and batching pipelines to work live
Try instead: cloud ASR services
No built-in diarization — cannot tell who is speaking, only what is being said
Try instead: pyannote + Whisper
Do Not Use For
It is an automatic speech recognition model only — it converts audio to text, not the reverse
Try instead: GPT-4o
Trained on speech data — cannot parse musical notes, chords, or instrument separation
Try instead: specialized music AI