OpenAI Whisper
Open-source speech recognition model
FreeAIVoiceOpen Source3 impressions
OpenAI Whisper is a free alternative to Otter.ai.
OpenAI Whisper is an open-source, multilingual speech-recognition model that transcribes, translates and identifies spoken language.
- for
- Developers building audio-enabled apps, researchers, and hobbyists needing speech-to-text.
- pricing
- open source
- license
- MIT
Key features
- Multilingual transcription — Transcribes speech in over 100 languages with a single model.
- Speech translation — Directly translates spoken audio into another language.
- Language identification — Detects the language spoken in an audio clip.
- Multiple model sizes — Tiny to large models trade off speed, accuracy and VRAM usage.
- Easy installation — Install via pip or from source; requires only Python, PyTorch and ffmpeg.
- Command-line tool — Provides a ready-to-use CLI for quick transcription of audio files.
Use cases
- Generate subtitles for videos in multiple languages
- Add voice commands to a mobile app
- Transcribe interview recordings for research
- Create real-time captions for live streams
- Build multilingual voice assistants
OpenAI Whisper vs alternatives
 OpenAI Whisper |  Otter.ai |  ElevenLabs |  Voice Calling SDK by Dyte | |
|---|---|---|---|---|
| Best for | Multilingual speech-to-text and translation | Hosted meeting transcription | AI voice generation | Live voice communication |
| Pricing | Open source | Subscription | Subscription | Subscription |
| DevHunt upvotes | 0 | 0 | 0 | 44 |
| Launched | — | — | — | May 2024 |
- OpenAI Whisper vs Otter.ai: Otter.ai is a hosted service focused on meeting notes, not an open-source model you run yourself.
- OpenAI Whisper vs ElevenLabs: ElevenLabs provides text-to-speech synthesis, the opposite direction of Whisper’s speech-to-text.
- OpenAI Whisper vs Voice Calling SDK by Dyte: Dyte’s Voice Calling SDK offers real-time call audio, not offline transcription.
OpenAI Whisper FAQ
How do I install Whisper?+
Run pip install -U openai-whisper and ensure ffmpeg is installed on your system.
What hardware do I need?+
Whisper runs on CPUs, but GPU acceleration (e.g., an NVIDIA A100) speeds up inference; model size determines VRAM requirements.
Which model should I choose?+
Use tiny or base for fast, low-resource use; medium or large for higher accuracy; large requires ~10 GB VRAM.
Can Whisper translate speech?+
Yes, the model can output translated text when given a translation task token.
Is there a CLI?+
Yes, the package includes a command-line interface for transcribing audio files directly.
What languages are supported?+
Whisper supports roughly 100 languages, with English-only variants for the smallest models.
Summarized by DevHunt from github.com · Oct 7, 2026. Details may change; check the official site.
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