Whisper Large v3
OpenAI's flagship open speech-to-text model. 100 languages, MIT license. The de-facto open ASR baseline.
Overview
OpenAI's flagship open speech-to-text model. 100 languages, MIT license. The de-facto open ASR baseline.
Family & lineage
How this model relates to others in its lineage. Family members share architecture and training-data roots; parent / children edges record direct distillation or fine-tune relationships.
Strengths
- MIT license
- 100-language coverage
- Industry baseline
Weaknesses
- No streaming-native variant
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| FP16 | 3.1 GB | 4 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Whisper Large v3.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Whisper Large v3?
Can I use Whisper Large v3 commercially?
What's the context length of Whisper Large v3?
Does Whisper Large v3 support images?
Source: huggingface.co/openai/whisper-large-v3
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Whisper Large v3 runs on your specific hardware before committing money.