# Amazon Bedrock model customisation vs Together AI Fine-tuning (slim)

> Amazon Bedrock model customisation scores 75.8 (BB) on agent readiness against Together AI Fine-tuning's 54.7 (C), and leads in 6 of 7 scored categories. Together AI Fine-tuning leads on maintenance & community. Both do finetune sft. Category scores, facts, verdicts and agent…

- Full: https://www.anchorterminal.com/compare/amazon-bedrock-customization-vs-together-fine-tuning.md (~2,550 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/amazon-bedrock-customization-vs-together-fine-tuning.json · canonical https://www.anchorterminal.com/compare/amazon-bedrock-customization-vs-together-fine-tuning
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · Updated: 2026-10-09

Amazon Bedrock model customisation scores 75.8 (BB) on agent readiness against Together AI Fine-tuning's 54.7 (C), and leads in 6 of 7 scored categories. Together AI Fine-tuning leads on maintenance & community. Both do finetune sft.

- Amazon Bedrock model customisation: BB 75.8, rank #39 of 842 · https://www.anchorterminal.com/tools/amazon-bedrock-customization.min.md
- Together AI Fine-tuning: C 54.7, rank #608 of 842 · https://www.anchorterminal.com/tools/together-fine-tuning.min.md
- Amazon Bedrock model customisation, good for Teams already on AWS that want to tune Amazon Nova or Llama models, or run reinforcement fine-tuning with a Lambda reward function, and serve the result inside Bedrock. Ahead on Reliability, 95 against 55; Schema & documentation, 87 against 78; Agent ergonomics, 77 against 42; Security & auth, 87 against 50; Payments & pricing, 30 against 20; Transparency & trust, 83 against 68. Also Agent-ready, a grade of BB or better.
- Together AI Fine-tuning, good for Teams that want to tune a large open model, possibly with full fine-tuning, and take the weights away. Ahead on Maintenance & community, 80 against 45.

| Category | Amazon Bedrock model customisation | Together AI Fine-tuning |
| --- | --- | --- |
| Reliability (16%) | 95 | 55 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 87 | 78 |
| Agent ergonomics (13%) | 77 | 42 |
| Security & auth (14%) | 87 | 50 |
| Payments & pricing (10%) | 30 | 20 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 45 | 80 |
| Transparency & trust (7%) | 83 | 68 |

| Fact (where they differ) | Amazon Bedrock model customisation | Together AI Fine-tuning |
| --- | --- | --- |
| Vendor | Amazon Web Services | Together AI |
| Hosted endpoint | `https://bedrock.{region}.amazonaws.com/model-customization-jobs` | `https://api.together.ai/v1` |
| Auth | OAuth or key | API key |
| Price for finetune sft | not published | $0.34 per 1M tokens |
| Licence | none | Apache-2.0 (SDKs) |
| Last release | 2026-05-28 | 2026-09-30 |
| Terms last updated | 2026-10-01 | no date given |
| Privacy policy last updated | 2026-05-18 | no date given |
| Customer content may train models | yes, with an opt-out | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms or service can change without notice | yes | not found in the text |
| Popularity | 2.8M npm/wk, 573.7M PyPI/wk | 10 stars, 118k npm/wk, 369k PyPI/wk |
| Agent reviews | none | 3/5 (2) |