Closed model API
AWS Bedrock alternatives
What are the alternatives to AWS Bedrock?
The realistic field is 2 other closed model apis plus the adjacent categories below. Which one fits depends on why you are leaving — cost, portability, evaluation discipline and operational envelope pull in different directions, and no single alternative wins on all four.
Why teams leave
- A customised model needed to be portable and Bedrock’s is not
- Provisioned throughput was costly for bursty traffic
- You wanted the fine-tuning step to produce an asset rather than a capability
Before you move: what AWS Bedrock is good at
One API across several model vendors, inside an AWS account, with the governance story already written. For an enterprise that needs to switch model providers without switching procurement, that is the whole value proposition.
Stay if
- You need several model vendors behind one contract
- AWS governance and billing integration is a requirement
- Provisioned throughput suits your traffic better than per-hour GPUs
What a migration actually involves
- 01
Bring the training data — the custom model itself cannot move.
- 02
Choose an open-weight base of comparable size to what you were customising.
- 03
Gate against the Bedrock model as baseline before cutting traffic over.
Direct alternatives
Same category, so the closest substitutes.
OpenAI fine-tuning
Fine-tuning of OpenAI’s own closed models, served only from OpenAI. The default first stop, and the thing most teams are trying to leave.
Onrup
Cost authorised before compute is leased, a blocking evaluation gate before deploy, and weights you can always download or publish. Head to head with AWS Bedrock.
Adjacent options
Different category, but frequently the right answer depending on why you are leaving.
Together AI
Managed fine-tuning platformA broad model API with fine-tuning attached, covering the widest catalogue of open-weight models of anyone in this set.
Fireworks AI
Managed fine-tuning platformInference, fine-tuning and evaluation behind one API, with fine-tuned adapters served at the same per-token rate as the base model.
Modal
Serverless GPU platformServerless compute for arbitrary Python, billed by the second. Not a fine-tuning product — a substrate you build one on.
Baseten
Serverless GPU platformModel deployment and serving with strong operational tooling, compliance posture and cold-start engineering.
Frequently asked questions
Why do teams leave AWS Bedrock?
A customised model needed to be portable and Bedrock’s is not; Provisioned throughput was costly for bursty traffic; You wanted the fine-tuning step to produce an asset rather than a capability.
What do I lose by moving away from AWS Bedrock?
One API across several model vendors, inside an AWS account, with the governance story already written. For an enterprise that needs to switch model providers without switching procurement, that is the whole value proposition.
Can I export my model from AWS Bedrock?
Custom models stay inside Bedrock.
Can I export a Bedrock custom model?
No. That is the structural difference, and it is the reason most people evaluating both are evaluating both.
Last verified 6 August 2026.
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