Updated October 25, 2026
· ~4 min read
For three years this comparison was a choice of models: OpenAI's on one side, Claude, Nova and the open-weight models on Bedrock on the other. That stopped being true on June 1, 2026, when GPT-5.5, GPT-5.4 and Codex became generally available on Amazon Bedrock. GPT-5.6 Sol, Terra and Luna followed in July, and the GPT-6 family (Astra, Sol, Luna and GPT-6.1 Sol) in September.
So the question is no longer "Bedrock or OpenAI". It is whether to reach OpenAI's models through OpenAI's own API, or through Bedrock alongside everything else Bedrock offers — and that is a decision about data handling, identity, billing, networking and model lifecycle more than about model quality.
This page compares the two paths as they stand in October 2026, with the details that change real architectures: which APIs each model supports on Bedrock, how cross-Region inference affects residency, whose deprecation schedule applies, and what you give up by not going direct.
The old argument for Bedrock was structural — data stays in your AWS account, IAM instead of API keys, PrivateLink, CloudTrail, one bill — and the old argument against it was that OpenAI's models weren't there. The second argument is gone. AWS's launch post for OpenAI models on Bedrock states that prompts and responses are not used to train models and are not shared with model providers, and that GPT-5.5 and GPT-5.4 are billed at the same per-token rate as OpenAI's own API with no additional fees. Two details matter more than they look. First, API surface: at launch the OpenAI models on Bedrock were reached through the Responses API; in August 2026 AWS added Converse and Chat Completions on the bedrock-runtime endpoint for the GPT-5.6 models, along with Geo and Global cross-Region inference. Support is per model, so read the model card rather than assuming. Second, lifecycle: Bedrock usually publishes its own minimum-availability dates, but GPT-6.1 Sol's card says it follows OpenAI's first-party deprecation terms instead, with no separate Bedrock date. Plan migrations on whichever schedule the card names.
Go direct when you depend on something that only exists on OpenAI's platform — a newly released model or feature before it reaches Bedrock, OpenAI-hosted tools, or the wider ChatGPT and OpenAI product surface. AWS has announced Bedrock Managed Agents powered by OpenAI as "coming soon", which is a fair signal that some OpenAI capabilities arrive on Bedrock after they arrive at OpenAI. Go direct, too, if you don't run on AWS: Bedrock's advantages are mostly about fitting into an AWS estate you already have.
Choose Bedrock when the workload touches regulated or customer data and your controls already live in AWS — IAM, CloudTrail, VPC endpoints, KMS and AWS Artifact are the same evidence your auditors already accept. Choose it when you want more than one model family: putting GPT-6 Sol, Claude Sonnet 5.5 and a small open-weight model behind one set of APIs, one bill and one set of guardrails is what lets you pick a model per task on cost and quality instead of per vendor contract. And choose it for coding agents: Codex through Bedrock is billed per token with no per-seat licenses, which changes the economics for a team where usage is uneven.
Starting points to evaluate on your own data — not benchmark claims. Every one of these is available on Bedrock.
Question 1 of 3
Do your applications and data already run on AWS?
If your systems already run on AWS, call OpenAI models through Bedrock by default: the same models, AWS's statement that prompts and responses are not shared with the model provider, IAM instead of a new API key, PrivateLink, CloudTrail and one bill — at the per-token prices AWS says match OpenAI's own. Go direct to OpenAI when you need a feature that exists only on OpenAI's platform, when you want new releases the day they ship, or when you're not on AWS at all. And the bigger win of the Bedrock path is optionality: Claude, Nova and open-weight models sit behind the same APIs and controls, so choosing a model per task becomes a configuration change instead of a second vendor integration.
Amazon Bedrock Enterprise AI Platform
A production AI platform on Amazon Bedrock: RAG pipelines, agent orchestration, guardrails, multi-tenant cost tracking, and the observability needed to run AI in production.
Bedrock Model Migration Sprint
Move every workload off a retiring Bedrock model before its end-of-life date (found across all your accounts, tested against your own traffic, rolled out in stages) and leave a lifecycle check behind so the next deadline isn't a surprise.
Secure LLM Gateway on AWS
One governed way for every team to call AI models: keys held centrally, budgets and rate limits per team, fallbacks between providers, and hardening that assumes the gateway is a target.
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As of October 25, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.