Side by side
Standard-tier prices in effect today. The better value in each row is highlighted.
| Fact | Gemini 3.1 Flash Live Preview | Gemini 3.5 Transcribe |
|---|---|---|
| Price per audio minute | $0.005 | $0.005 |
| Artificial Analysis AA-WER v2 | Not measured | 2.6 % WER (#4 of 6) |
| Provider | ||
| Release date | March 26, 2026 | August 26, 2026 |
| Access | API only | API only |
| Context window | 131,072 tokens | Not reported |
| Max output | 65,536 tokens | Not reported |
| Input | text, image, audio, video | audio |
| Output | text, audio | text |
When to choose each
Gemini 3.1 Flash Live Preview
Best for
- Realtime voice applications with multimodal context
Watch out for
- This preview endpoint may change before becoming stable and has input prices that vary by modality
Gemini 3.5 Transcribe
Best for
- Batch transcription with speaker labels
- Multilingual meeting and call transcripts
Watch out for
- One hour of audio per request, or 30 minutes with diarization or timestamps
- Custom vocabulary cannot be combined with diarization or timestamps, and there is no Batch API
Gemini 3.1 Flash Live Preview vs Gemini 3.5 Transcribe FAQ
Which is cheaper, Gemini 3.1 Flash Live Preview or Gemini 3.5 Transcribe?
Both cost $0.005 per audio minute.
Related comparisons
- Gemini 3.1 Flash Live Preview vs Gemini 3.8 Flash-Lite TTS
- Gemini 3.1 Flash Live Preview vs Gemini 3.8 Flash TTS
- Gemini 3.1 Flash Live Preview vs Gemini 3.8 Live
- Gemini 3.1 Flash Live Preview vs GPT-4o Transcribe
- Gemini 3.1 Flash Live Preview vs GPT Transcribe
- Gemini 3.1 Flash Live Preview vs Scribe v2 Realtime
- Gemini 3.5 Live Translate Preview vs Gemini 3.5 Transcribe
- Gemini 3.5 Transcribe vs Gemini 3.8 Flash-Lite TTS
- Gemini 3.5 Transcribe vs Gemini 3.8 Flash TTS
- Gemini 3.5 Transcribe vs Gemini 3.8 Live
Production evaluation
Choosing between Gemini 3.1 Flash Live Preview and Gemini 3.5 Transcribe?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty
