OpenAI’s transcription docs repeat GPT-Transcribe’s benchmark gains over Whisper
OpenAIDevs · x · 2026-07-29
This reply points back to OpenAI’s transcription docs and repeats the key benchmark figures for GPT-Transcribe:
- 41.6% → 45.2% semantic accuracy on Context Aware ASR when free-form context is added.
- 19.27% WER on Common Voice across 22 languages, versus 40.37% for Whisper.
- 8.98% WER on Real-World Audio Recording across 9 languages, versus 15.21% for Whisper.
It’s essentially the documentation trail for the new transcription API launch.
Related event: OpenAI Launches Two New Voice Transcription Models(4 posts)→
More from Models
- Are AI Models Hitting a Wall? Debate Sparks Over Loss of Generality — JacquesThibs · 2026-07-29
- Kimi K3 Takes #1 in Code Arena Fullstack, Beating GPT-5.6 and Claude — KickLassChewGum · 2026-07-29
- Kimi K3 is the First Open-Source Model to Pass Compound's Internal Benchmark — peterjliu · 2026-07-29
- Claude Opus 5 tops LisanBench while using far fewer tokens in medium mode — scaling01 · 2026-07-29
- Bindu Reddy says OpenAI and Anthropic are fear-mongering over Kimi K3 — bindureddy · 2026-07-29
- Claude CoT leak joke turns Anthropic’s “openness” into a model-bashing meme — OwariDa · 2026-07-29