whisper-medium
Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.
Params
760 M
Context
—
Downloads 30d
378 K
Likes
296
Download history
daily snapshots · 56 days
▲ 11 K in the last 30 days (2.9%)
389 K378 K
Aug 23Sep 2Sep 12Sep 21
397 K342 K
Jul 28Aug 15Sep 3Sep 21
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 3.1 GB | 4.0 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- WhisperForConditionalGeneration
- Parameters
- 760 M
- Tensor type
- F32
- Vocabulary
- 51,865
- Licence
- apache-2.0
- First seen on the Hub
- 2022-09-26
- Training datasets
- undisclosed
- Common Voice 11.0 (reported)
- 53.87
- LibriSpeech (clean) (reported)
- 2.9
- LibriSpeech (other) (reported)
- 5.9
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any automatic-speech-recognition model