Whisper Large v3 (ONNX)
Production-ready ONNX conversion of openai/whisper-large-v3 for high-quality multilingual speech recognition — converted for edge deployment via Edgework.ai.
Highlights
- Best-in-class multilingual ASR — OpenAI's flagship speech model
- 1.5B parameters — maximum quality for 99+ languages
- Trained on 1M+ hours of weakly-supervised audio
- Versatile — transcription, translation, language detection, timestamps
Model Details
| Property | Value |
|---|---|
| Base model | openai/whisper-large-v3 |
| Parameters | 1.5B |
| Languages | 99+ |
| Input | 16 kHz audio |
| Tasks | Transcription, translation, language ID, timestamps |
| License | Apache 2.0 |
Use Cases
This model powers premium speech recognition in Edgework.ai — bringing fast, cheap, and private inference as close to the user as possible. Choose this when quality is paramount:
- Professional transcription of therapy/coaching sessions
- High-accuracy multilingual emotion journaling
- Meeting transcription with speaker diarization
- Subtitle generation for wellness content
Related Models
| Model | Parameters | Languages | Use case |
|---|---|---|---|
| whisper-small-onnx | 244M | 99 | Lightweight multilingual |
| whisper-large-v3-onnx | 1.5B | 99+ | Best multilingual quality |
| whisper-large-v3-turbo-onnx | 809M | 99+ | Fast, high-quality |
| parakeet-ctc-0.6b-onnx | 0.6B | English | Best English-only ASR |
About
Published by AFFECTIVELY · Managed by @buley
We convert, quantize, and publish production-ready ONNX models for edge and in-browser inference. Every release is tested for correctness and stability before publication.
- All models · GitHub · Edgework.ai
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Model tree for affectively-ai/whisper-large-v3-onnx
Base model
openai/whisper-large-v3