openai / automatic-speech-recognition updated 1 year ago

whisper-large-v3-turbo

Name: whisper-large-v3-turbo
Author: openai

Whisper is a state-of-the-art model for automatic speech recognition (ASR) and speech translation, proposed in the paper Robust Speech Recognition via Large-Scale Weak Supervision by Alec Radford et al. from OpenAI. Trained on >5M hours of labeled data, Whisper demonstrates a strong ability to generalise to many datasets and domains in a zero-shot setting.

Params

810 M

Context

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Downloads 30d

8.7 M

Likes

3,223

Commercial use: allowed mit Not gated SAFETENSORS 99 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

8.7 M8.5 M

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	f16	1.6 GB	2.4 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: 810 M
Tensor type: F16
Vocabulary: 51,866
Licence: mit
First seen on the Hub: 2024-10-01
Base model: whisper-large-v3
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

Base model and the most-downloaded derivatives in the catalog.

Base whisper-large-v3 openai 5.5 M

Compare with

speaker-diarization-3.1 8.9 M whisperkit-coreml 8.3 M speaker-diarization-community-1 5.3 M wav2vec2-large-xlsr-53-portuguese 4.6 M Qwen3-ASR-0.6B 4.3 M wav2vec2-large-xlsr-53-russian 4.0 M

Appears in

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