Best Speech-to-text APIs for Meetings (2026)
For meetings, AssemblyAI is our pick: For transcribing recorded meetings and interviews, speaker diarization is the top priority. Transcribing recorded meetings and interviews, where speaker labels, summaries, and long-file handling matter more than latency. Below is the full ranking and the tradeoffs, or read how we score.
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Reviewed by vsref Editorialfacts verified Jul 24, 2026Methodology →
AssemblyAIWINNER
What matters for meetings
Weight ×5 = decisive, ×1 = relevant| Fact | AssemblyAI | ElevenLabs Scribe | Gladia | Amazon Transcribe | OpenAI gpt-4o-transcribe |
|---|---|---|---|---|---|
| Speaker diarization×5 | ◑ Paid add-onJul 20 | ✓ IncludedJul 20 | ✓ IncludedJul 20 | ✓ IncludedJul 20 | ✓ IncludedJul 20 |
| Summarization endpoint×4 | ✓ YesJul 20 | n/a | ✓ YesJul 20 | ✓ YesJul 20 | ✗ NoJul 20 |
| Languages supported×3 | 99Jul 20 | 90 languagesJul 20 | 101 languagesJul 20 | 113 languagesJul 20 | 57 languagesJul 20 |
| Max file size / duration×3 | 5 GB / 10 hr per file; 2.2 GB via upload endpointJul 20 | 3 GB / 10 hr per fileJul 20 | 1000 MB; 135 min per request (4h15 Enterprise)Jul 20 | 2 GB and 28,800 s (8 h) max per batch fileJul 20 | 25 MB max upload; no duration limit statedJul 20 |
| Word-level timestamps×2 | ✓ YesJul 20 | ✓ YesJul 20 | ✓ YesJul 20 | ✓ YesJul 20 | ✗ NoJul 20 |
The ranking, tool by tool
For transcribing recorded meetings and interviews, speaker diarization is the top priority. Full AssemblyAI vs OpenAI Whisper (API) verdict →
For recorded meetings, speaker diarization carries the heaviest weight. Full AssemblyAI vs Speechmatics verdict →
For recorded meetings and interviews, speaker diarization and summarization carry the most weight. Full AssemblyAI vs Soniox verdict →
For meeting transcription, speaker diarization is the top-weighted factor. Full AssemblyAI vs Rev AI verdict →
For recorded meetings, speaker diarization is the top priority. Full AssemblyAI vs Gladia verdict →
For recorded meetings, speaker diarization is the top priority. Full AssemblyAI vs Deepgram verdict →
For meeting transcription, speaker diarization is the single most important attribute. Full ElevenLabs Scribe vs OpenAI Whisper (API) verdict →
Both tools include speaker diarization at no extra cost, so that attribute is a wash. Full ElevenLabs Scribe vs Mistral Voxtral Transcribe verdict →
For recorded meetings, speaker diarization is the heaviest factor, and Gladia includes it while OpenAI Whisper (API) does not. Full Gladia vs OpenAI Whisper (API) verdict →
For meeting transcription, speaker diarization carries the most weight. Full Gladia vs Deepgram verdict →
Both tools include speaker diarization, so the heaviest attribute is a draw. Full Amazon Transcribe vs Google Cloud Speech-to-Text verdict →
For meeting transcription, speaker diarization is the most critical attribute. Full OpenAI gpt-4o-transcribe vs OpenAI Whisper (API) verdict →
Both tools score identically on the two heaviest attributes: neither supports speaker diarization and neither offers a summarization endpoint, so those decisive criteria cancel out. Full Groq (hosted Whisper) vs OpenAI Whisper (API) verdict →
Speaker diarization, the heaviest attribute at weight 5, goes decisively to NVIDIA Parakeet / Riva, which includes diarization natively, while OpenAI Whisper API offers none. Full NVIDIA Parakeet / Riva vs OpenAI Whisper (API) verdict →
For transcribing recorded meetings, speaker diarization is the heaviest factor. Full Smallest.ai Pulse vs Deepgram verdict →
For meetings, speaker diarization is the top-weighted factor. Full Deepgram vs Mistral Voxtral Transcribe verdict →
For transcribing recorded meetings, speaker diarization is the heaviest factor, weighted 5 out of 5. Full Deepgram vs OpenAI Whisper (API) verdict →
For meeting transcription, speaker diarization and summarization are the two heaviest factors. Full Deepgram vs Soniox verdict →
For meetings, speaker diarization and summarization carry the most weight. Full Deepgram vs Google Cloud Speech-to-Text verdict →
For recorded meetings and interviews, speaker diarization is the single most important attribute. Full Deepgram vs Cohere Transcribe verdict →
For transcribing recorded meetings and interviews, speaker diarization is the most critical feature. Full Deepgram vs Cartesia Ink verdict →
On the two heaviest attributes, both tools tie: speaker diarization is included in both at no extra charge, and neither offers a summarization endpoint. Full Azure AI Speech (STT) vs Google Cloud Speech-to-Text verdict →
For meeting transcription, speaker diarization is the most critical attribute, and Mistral Voxtral Transcribe includes it natively while OpenAI Whisper offers none. Full Mistral Voxtral Transcribe vs OpenAI Whisper (API) verdict →
For recorded meetings, speaker diarization is the top priority. Full Speechmatics vs Deepgram verdict →
On-device streaming STT for live voice interfaces, from tiny edge models to Whisper Large v3-beating accuracy. No won verdicts for this use case yet; it ranks on ties and near-misses.
Open-weights multilingual ASR models. No won verdicts for this use case yet; it ranks on ties and near-misses.
Low-cost pay-as-you-go file transcription from OpenAI; no first-party streaming or diarization. No won verdicts for this use case yet; it ranks on ties and near-misses.
Streaming STT for voice agents with native turn detection. No won verdicts for this use case yet; it ranks on ties and near-misses.
Enterprise-grade open ASR for accurate batch transcription. No won verdicts for this use case yet; it ranks on ties and near-misses.
Hyperscaler STT API with Chirp foundation models and enterprise compliance. No won verdicts for this use case yet; it ranks on ties and near-misses.
Transcription-heritage STT API with low per-hour pricing and open (non-commercial) Reverb models. No won verdicts for this use case yet; it ranks on ties and near-misses.
Ultra-low-cost multilingual STT + real-time translation API. No won verdicts for this use case yet; it ranks on ties and near-misses.