openai / automatic-speech-recognition updated 2 years ago

whisper-medium

Name: whisper-medium
Author: openai

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

364 K

Likes

293

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 99 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

364 K352 K

Jul 28Jul 31Aug 3Aug 6

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.

Derivative whisper-medium-gguf handy-computer 518 K

Compare with

speaker-diarization-3.1 8.9 M whisper-large-v3-turbo 8.7 M whisperkit-coreml 8.3 M speaker-diarization-community-1 5.3 M whisper-base 4.8 M wav2vec2-large-xlsr-53-portuguese 4.6 M

Appears in

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