Every time somebody questions why you might "trust" AWS (or Azure or GCP or whatever), or why you'd pay this premium, I realize they are not accustomed to working in enterprise environments.

In my case, I work at a large enterprise with strict data governance built into customer contracts, and (partly related, partly not) our own governance concerns. Using vendors where you not only have infosec permission, but they are also listed as data processors in our contracts with our customers is the way not to get fired and sued.

If I'm playing around at home, with my own code and data, I can do whatever I want. But with my employer and customer? Absolutely not. It's the same reason we don't use whatever is the flavor of the month frontier model is.

Side hustles and startups just have an entirely different set of constraints and considerations.

If you've used AI coding models in a large corporate setting, you'll know that a lot of big corporate deployments basically require using AWS Bedrock for two simple reasons:

1. Large companies tend to already have an existing relationship with AWS, which makes things way easier to go through vs. setting up a new vendor relationship 2. Large companies tend to have strong internal requirements about making sure that internal data stays under company control. With AWS Bedrock, you can be a lot more confident that what you're feeding into the models is not going to end up in someone's training set somewhere. For where I work, this requirement is a dealbreaker for going directly through OpenAI's API instead of going through AWS Bedrock.

If you are wondering why anyone would spend more money to use these APIs through AWS instead of going direct: In some companies it’s nearly impossible to get new vendors approved. If the company has an AWS contract then you have to use what AWS offers.

This is the best thing to happen to AwS. Aws won't push their junk Bedrock equivalents at least.

Enterprises can focus on paying for AWS OpenAI models and get going.

Frontier labs provide “frozen” builds of their models that hyperscalers just serve without collecting data. This is a prerequisite from most of the companies that store sensitive data and still want to use frontier LLMS.

This is a great move for OpenAI and one that should worry Anthropic. Bedrock was the only way I could use foundation models for a while given AWS lock-in and security requirements.

Absolutely huge news for OpenAI. Unimaginable amount of enterprises picked up Claude just because it was available in AWS, and now there's serious competition.

Anthropic better get that IPO out soon. Their incredible revenue run-up was basically a result of botched Gemini releases and OpenAI having their hands-tied behind their Azure backs.

Anthropic models were quite literally the only viable serverless API (i.e. Bedrock) models on AWS. They didn't even bother releasing the recent Qwen 3.5/3.6 series. Combined with the token efficiency/ROI focus, I would really like to see how Antrhopic ends Q3.

Sucks for Azure. They were the chosen one but couldn’t keep up with demand. Once OpenAI got out of that exclusivity deal saying Azure wasn’t reliable I knew AWS was where they were headed.

Good news for competition.

Claude Code keeps omitting new features from people using it through Amazon Bedrock (e.g. auto mode, ultra plan, Claude for Chrome). Hopefully some more competition can get them to rethink their strategy.

Are they? I don't see them in the Model Catalog on Bedrock.

This is great news. I wish they were keeping their other models updated. With Gemma 4 and Qwen 3.7 already available on OpenRouter, bedrock is just not keeping up at all.

great for consumers, great for OpenAI, great for Amazon, not so great for MS / Azure (seems like they don't care anyways)

As usual the more options the better for everyone. While this is not a direct replacement it is good that it exists.

No 5.5 Pro

More expensive than directly sourcing from OpenAI