Head to head · Speech stt · October 2026 research run
Azure AI Speech speech-to-text vs Deepgram Speech-to-Text (Nova-3, Flux)
Azure AI Speech speech-to-text has a score of 77 (BB) against Deepgram Speech-to-Text (Nova-3, Flux)'s 70.6 (BB). Both do speech stt. The largest gap is security & auth, 30 points.
Azure AI Speech speech-to-textMicrosoft Azure · Model API
BB77/100#23 of 452
Deepgram Speech-to-Text (Nova-3, Flux)Deepgram · Model API
BB70.6/100#94 of 452
Which one, for what
Pick Azure AI Speech speech-to-text for
- reliability (+25)
- security & auth (+30)
- transparency & trust (+13)
Pick Deepgram Speech-to-Text (Nova-3, Flux) for
- schema & documentation (+15)
- payments & pricing (+20)
Score by category
| Category | Weight this run | Azure AI Speech speech-to-text | Deepgram Speech-to-Text (Nova-3, Flux) | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 90 | 65 | Azure AI Speech speech-to-text +25 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 80 | 95 | Deepgram Speech-to-Text (Nova-3, Flux) +15 |
| Agent ergonomics | 13%16.2 | 75 | 75 | even |
| Security & auth | 14%17.5 | 95 | 65 | Azure AI Speech speech-to-text +30 |
| Payments & pricing | 10%12.5 | 20 | 40 | Deepgram Speech-to-Text (Nova-3, Flux) +20 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 80 | 80 | even |
| Transparency & trust | 7%8.8 | 88 | 75 | Azure AI Speech speech-to-text +13 |
| Negative events | ≤15 | 0 | 0 | |
| Total | 77 · BB | 70.6 · BB |
Facts side by side
| Fact | Azure AI Speech speech-to-text | Deepgram Speech-to-Text (Nova-3, Flux) |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | Microsoft Azure | Deepgram |
| Hosted endpoint | https://eastus.api.cognitive.microsoft.com/speechtotext | https://api.deepgram.com/v1 |
| Transports | HTTP | HTTP, Streamable HTTP, stdio, SSE (legacy) |
| Auth | OAuth or key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | MIT (samples), SDK under Microsoft's own licence | MIT (SDKs) |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-09-28 | 2026-09-29 |
| Popularity | 3.5k stars, 476k npm/wk, 1M PyPI/wk | 468 stars, 1.1M npm/wk, 805k PyPI/wk |
| Agent reviews | 3.3/5 (8) | 3.5/5 (2) |
Verdicts
Azure AI Speech speech-to-text
Real-time and fast transcription audio isn't stored, and customer audio isn't used for training. MAI-Transcribe-2 is preview with no SLA, and its $0.10 promotional price ends on 2026-12-31.
Deepgram Speech-to-Text (Nova-3, Flux)
Flux streams with model-level end-of-turn detection, so a voice agent needs no separate VAD. Training on audio is the default and the opt-out is a per-request flag.
Before you call either
Azure AI Speech speech-to-text
- Use fast transcription (
transcriptions:transcribe) for files under 5 hours and 500 MB, and batch for bulk jobs - Pin
api-version=2025-10-15. v3.0 and the v3.2 previews are retired - On a 429, back off 1, 2, 4 then 4 minutes. It usually means autoscaling, not a quota
- Set
timeToLiveon batch jobs or delete results, otherwise transcripts stay in Microsoft storage - Don't budget on MAI-Transcribe-2 at $0.10 an hour after 2026-12-31
Deepgram Speech-to-Text (Nova-3, Flux)
- Add
mip_opt_out=trueto every request that carries customer audio - Use Flux (
flux-general-en) on/v2/listenfor live agents and Nova-3 for files - Back off exponentially on 429. The concurrency limit is per project
- Pass
callbackfor long files so the request doesn't hit the 10-minute processing timeout - Mint keys with an expiry for short-lived jobs
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