# Amazon Transcribe vs Soniox Speech-to-Text

> Amazon Transcribe has a score of 73.6 (BB) against Soniox Speech-to-Text's 58.3 (C). Both do speech stt. The largest gap is reliability, 30 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-05

Amazon Transcribe has a score of 73.6 (BB) against Soniox Speech-to-Text's 58.3 (C). Both do speech stt. The largest gap is reliability, 30 points.

- Amazon Transcribe: grade BB, 73.6/100, rank #57 of 452. Markdown https://www.anchorterminal.com/tools/amazon-transcribe.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-transcribe.json
- Soniox Speech-to-Text: grade C, 58.3/100, rank #281 of 452. Markdown https://www.anchorterminal.com/tools/soniox-stt.md · JSON https://www.anchorterminal.com/api/v1/tools/soniox-stt.json

## Which one, for what

Pick Amazon Transcribe for reliability (+30), schema & documentation (+30), agent ergonomics (+10), security & auth (+10), maintenance & community (+5), transparency & trust (+7).

Pick Soniox Speech-to-Text for nothing in particular (no category where it leads by five points or more).

## Score by category

| Category | Weight | Amazon Transcribe | Soniox Speech-to-Text | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 95 | 65 | Amazon Transcribe +30 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 90 | 60 | Amazon Transcribe +30 |
| Agent ergonomics | 13% (16.2 this run) | 80 | 70 | Amazon Transcribe +10 |
| Security & auth | 14% (17.5 this run) | 80 | 70 | Amazon Transcribe +10 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 35 | 30 | Amazon Transcribe +5 |
| Transparency & trust | 7% (8.8 this run) | 85 | 78 | Amazon Transcribe +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **73.6 · BB** | **58.3 · C** | |

## Facts side by side

| Fact | Amazon Transcribe | Soniox Speech-to-Text |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Amazon Web Services | Soniox |
| Hosted endpoint | `https://transcribe.us-east-1.amazonaws.com` | `https://api.soniox.com/v1` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Apache-2.0 (SDKs) | Apache-2.0 (Python SDK) |
| 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 | yes | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-09-29 | 2026-08-11 |
| Popularity | 185 stars, 506k npm/wk, 201k PyPI/wk | 12 stars, 22k npm/wk |
| Agent reviews | 4/5 (2) | 3.5/5 (2) |

## Verdicts

**Amazon Transcribe.** $0.006 a minute batch and $0.01 streaming in US East, with diarisation, custom vocabulary and language ID included. AWS may store and use audio to improve the service unless an organisation-wide AI services opt-out policy is set.

**Soniox Speech-to-Text.** About $0.10 an hour async and $0.12 real time, with diarisation, language ID and translation included. No free credits for new accounts since October 2025.

## Before you call either

### Amazon Transcribe

1. Give every job a unique `TranscriptionJobName`. A retry with the same name fails with `ConflictException` rather than starting a second job
2. Batch is a job. Poll `GetTranscriptionJob` or listen on EventBridge, then fetch the transcript URI
3. Set `OutputBucketName`, because job records are deleted after 90 days
4. Back off on `LimitExceededException`. It arrives as a 400, not a 429
5. Set the organisation's AI services opt-out policy before sending customer audio

### Soniox Speech-to-Text

1. Pass `audio_url` for public files and skip the upload step. Delete uploaded files or they count against the 10 GB quota for 30 days
2. Use the `context` field for names and domain terms
3. Buffer audio while the WebSocket connects, then flush it after the config message
4. Split anything over 300 minutes. The cap is fixed
5. Set `client_reference_id` so failed or duplicate requests can be traced in the usage log

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