OpenAI Whisper

Whisper is OpenAI’s open-source automatic speech recognition system supporting 99 languages with robust, human-level transcription accuracy.

Overview

Whisper is OpenAI’s general-purpose speech recognition model, trained on 680,000 hours of multilingual audio. It handles transcription, translation, and language identification across 99 languages with remarkable robustness to accents, background noise, and technical jargon. Released as open source under MIT license, it runs locally and powers countless transcription applications.

The model family ranges from tiny to large, balancing speed and accuracy for different hardware. Whisper’s zero-shot transfer capabilities make it reliable across diverse domains without fine-tuning, and its release catalyzed the open speech recognition ecosystem.

Whisper’s robustness is its reputation: accents, background noise, and technical vocabulary that break smaller systems are handled with graceful degradation. The community ecosystem — faster-whisper, whisper.cpp, cloud wrappers — means deployment options for every environment from phones to servers.

Key Features

• Speech recognition across 99 languages
• Speech translation to English
• Robust performance on accents and noisy audio
• MIT-licensed open-source model weights
• Multiple model sizes from tiny to large
• Zero-shot domain transfer without fine-tuning
• Active community with faster implementations (faster-whisper)
• Graceful degradation on accents, noise, and technical vocabulary
• Rich community ecosystem with optimized implementations

Pricing

Whisper is completely free and open source under the MIT license. Users can download models and run them locally without any fees. OpenAI also offers hosted Whisper API access at approximately $0.006 per minute. Self-hosting costs only compute, making Whisper essentially free at scale for organizations with engineering resources to deploy it.

Who Is It For

Whisper is built for developers, researchers, and organizations that need reliable speech recognition without vendor lock-in or ongoing costs.

It is ideal for building transcription features into applications.

Journalists and researchers use Whisper to transcribe interviews and archival recordings in languages commercial tools support poorly.

FAQ

Is Whisper free to use?

Yes — the open-source model is free under MIT license; OpenAI’s hosted API is available at $0.006/minute for those preferring cloud processing.

Does Whisper offer an API?

Yes — OpenAI provides a hosted Whisper API, and the open-source model can be self-served through community tools.

How does Whisper compare to Deepgram or AssemblyAI?

Whisper is free and open-source with broad language support, Deepgram offers real-time streaming APIs, and AssemblyAI adds speaker diarization and summarization features.

How accurate is Whisper on noisy audio?

Whisper is notably robust on noisy, accented, and challenging audio compared with many systems, though very heavy noise or overlapping speakers still reduce accuracy as with all speech recognition.