Whisper (OpenAI)

Basic Information

• Developer: OpenAI
• Country/Region: United States
• Official Website: https://openai.com/index/whisper/
• GitHub: https://github.com/openai/whisper
• Type: Speech-to-Text (STT) / Automatic Speech Recognition (ASR)
• First Release: September 2022
• Latest Version: Whisper V4 (Released by the end of 2025)
• License: MIT
• HuggingFace: https://huggingface.co/openai/whisper-large-v3

Product Description

Whisper is an open-source automatic speech recognition system developed by OpenAI, trained on 680,000 hours of multilingual and multitask web audio data through large-scale weakly supervised learning. Whisper supports speech-to-text in over 50 languages and can handle accents, background noise, and technical jargon. Whisper V4 (released by the end of 2025) introduces native speaker diarization and real-time streaming capabilities, achieving a Word Error Rate (WER) of approximately 3.2% for English audio, nearing human professional levels (typically 4-5% WER).

Core Features/Characteristics

• Multilingual Support: Supports speech recognition and translation in over 50 languages
• High Accuracy: English WER of approximately 3.2%, nearing human professional levels
• Speaker Diarization: V4 introduces native speaker diarization capabilities
• Real-Time Streaming: V4 supports real-time streaming speech-to-text
• Noise Robustness: Excellent background noise handling capabilities
• Multiple Model Options: tiny, base, small, medium, large, turbo, and more
• Turbo Model: Optimized version of large-v3, faster with minimal precision loss
• Local Operation: Can run on local devices without requiring cloud API

API Evolution

• gpt-4o-transcribe: Released in March 2025, with lower error rates than Whisper
• gpt-4o-mini-transcribe: OpenAI's currently recommended best transcription model
• Whisper API: Calls the Whisper model via the OpenAI API

Business Model

• Free Open-Source Model: MIT license, free for local use
• Pay-as-you-go API: $0.006/minute (Whisper API)
• gpt-4o-transcribe API: Higher rates but better accuracy

Market Performance

• Over 75k GitHub Stars
• Benchmark product in the open-source speech recognition field
• Widely integrated into numerous applications and services
• Achieved 98% accuracy in 2026 benchmark tests

Relationship with the OpenClaw Ecosystem

Whisper serves as the speech-to-text engine for OpenClaw. OpenClaw uses Whisper to convert user voice inputs into text, enabling AI agents to interact via voice. Whisper's local operation capability ensures the privacy and security of voice data, while its multilingual support allows OpenClaw to serve global users. Real-time streaming capabilities support real-time voice conversation scenarios.