OpenAI vs Google
OpenAI gpt-transcribe vs Google Gemini 3 Flash for transcription. WER: 3.3% vs 2.9% — edge Google Computed from public benchmarks with dated sources; updated 2026-08-20.
Head to head
| Axis | OpenAI gpt-transcribe | Google Gemini 3 Flash | Edge |
|---|---|---|---|
| Price | $4.5 per 1000 min | $1.92 per 1000 min* | — |
| WER | 3.3% | 2.9% | |
| Langs | — | — | — |
| Latency | — | — | — |
| diarization | — | — | — |
| timestamps | — | — | — |
| vocab | ✓ | — | — |
* token-/credit-priced — the headline understates real per-unit cost, so no price edge is awarded.
Strengths & caveats
OpenAIOpenAI's current recommended transcription model: both cheaper ($4.50/1000 min) and more accurate (3.3% WER) than the gpt-4o-transcribe tier it supersedes, with a keywords parameter for biasing terms. Returns plain JSON: no word-level timestamps (only the legacy whisper-1 emits them) and no native diarization — OpenAI ships a separate gpt-4o-transcribe-diarize model for speaker labels. Also billed per token as an alternative to the per-minute rate.GoogleStrong accuracy (2.9% WER) and broad multilingual coverage as part of a multimodal model. Speech-to-text is a feature of a general LLM, not a dedicated transcription API: no native diarization, word-timestamps or custom vocabulary. The $1.92/1000 min is input-audio tokens only (output transcript billed separately), so it is not directly comparable to per-minute STT pricing.
Sources
- Artificial Analysis — Speech to Text2026-08-20
- Open ASR Leaderboard2026-06-19