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.
Have you considered checking the actual AWS contract and the limited liability they explicitly stipulate in contracts and even linked docs from marketing materials?
If you read the fine print, you'll notice something funny. You are largely responsible for data loss, SLA claims require you to present concrete evidence, and the remediation you accepted is usually credits for future spend on specifically the same product you lost your data on.
And AWS fine print is actually quite reasonable compared with, say, GCP, where the SLA seems mostly useful so the enterprise acquisition team can say "they have SLA, I can't get fired for choosing them since I did my due diligence!", while GCP can say "you already accepted the proposed remedy when signing the contract, sue us and we'll just point you to it. Thanks for your trust.". [0]
^ Standard multi-region or dual-region storage has a 99.95% availability SLA, regional Standard has 99.9%, and regional Nearline, Coldline, or Archive can be as low as 99.0%. The credits are 10%, 25%, or 50% of the monthly bill for the affected service tier, with 50% as the aggregate monthly cap, applied to future use. Google also says the customer must request the credit within 30 days or forfeit it.
On top of this, there's a vast difference between "what do you mean that team spent $1000 on AI in their expense report, what did we get for that?" vs. "oh, the company-wide AWS bill went up by a few percent, let's look into that when we have time." The latter makes projects far more viable.
The security posture at AWS is different. AI startups are going to get hacked and leak data etc. All the startup webapp builder tools, vscode plugin players etc.
AWS could still be hacked, but they've taken some care to make it a bit less likely, a bit easier to track which customers affected etc. If you dig into AWS logging for example, there is a TON if you turn it on, you can really go back and see who did what to the permissions / environment etc. I imagine they've got pretty good logging of their staffs access to things as well. I had to jump through some hoops once to have their staff on my account.
I have just moved from a free environment in which I was able to use any AI harnesses or models to a strict enterprise environment.
I was shocked to realize how difficult it has been to have a GitHub CoPilot license on Azure. I mean, they're both Microsoft products. But no, the IT now has to figure out how to set up a GitHub enterprise, link to Azure subscription, and all that.
Yeah, cloud agents come with nice things like being able to filter content, implement guardrails like preventing PII or prompt injection from taking place. even if they sucked, at least liability wise you're set. I don't know how someone could even come close to this capability by doing it on their own. If anyone does, please share what tools, platforms and projects you're using.
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.
To go a step further, the reason it's often impossible to add a new vendor if that you've signed a bunch of contracts with your customers saying you're not going to send their data to other vendors in all sorts of various flavors.
3. from my opportunity - For many (not all) LLMs, Bedrock gives you control over which country the data stays in. You have no control over that with the Claude API, for example. We do not work in the US and have strong requirements for the data to stay in our country, which Bedrock gives us control over.
Curious to understand how AI will continue to grow if this is the trend. Assuming most valuable data is behind such firewalls. And whatever is public has been harvested, trained on top of whatever has been acquired illegally (this is a grey area).
Will it become a closed ecosystem without outside input?!
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.
Even if you can get it approved you are adding surface area to your annual security audits, adding another vendor that needs to be disclosed on security assessments, spreading your data to yet another processor, and adding another invoice and budget discussion. Depending on your customer contracts you may need to notify them of a new vendor. This might trigger a new security review. Oh it’s just another model on Bedrock? Bliss.
Every CEO, board, and middle manager in the world is AI buzzword-obsessed now. Surely asking to sign a contract with the frontier labs directly would not get held up?
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.
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.
Claude is already available as both a pass-through to Anthropic's servers from AWS and in Bedrock. https://aws.amazon.com/claude-platform/ I imagine they're not thrilled that their first mover advantage has gone now, but they'll have seen it coming a mile off.
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.
It's so odd, because Claude models on Amazon Bedrock do support all those features.
For awhile now, I've had a api.anthropic.com emulator that "secretly" forwards requests to Amazon Bedrock. Works great and now I get all the nice first-party only features right away.
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.
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 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.
was only a matter of time. enterprise teams on aws werent going to rearchitect their stack just for model access, easier to bring the models to where the workloads already are
It's fascinating that cloud providers like AWS/GCP/Azure are now immovable "enterprise" technologies, in the way that IBM, Oracle, SAP, etc. were 15 years ago (and still are!).
Fond memories when only startups used S3 and EC2....
It's both an incredible triumph and tremendously sad that cloud providers are now the dinosaurs. So many companies are locked in, just as they were before. It's only going to get worse.
But their contract with Microslop prevents this?!?!? They specifically said like a month ago that they wouldn’t sell API access on AWS, they would only release specific products.
The AWS pricing page says 10% more than OpenAI, which is probably because they’re forcing all inference through the US and data residency is at a 10% premium from the model vendors for whatever reason (because you’ll pay for it).
If they put in a global endpoint like with Claude (or OpenAI directly) then it’ll probably match the direct pricing, if the pattern holds.
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.
Have you considered checking the actual AWS contract and the limited liability they explicitly stipulate in contracts and even linked docs from marketing materials?
If you read the fine print, you'll notice something funny. You are largely responsible for data loss, SLA claims require you to present concrete evidence, and the remediation you accepted is usually credits for future spend on specifically the same product you lost your data on.
And AWS fine print is actually quite reasonable compared with, say, GCP, where the SLA seems mostly useful so the enterprise acquisition team can say "they have SLA, I can't get fired for choosing them since I did my due diligence!", while GCP can say "you already accepted the proposed remedy when signing the contract, sue us and we'll just point you to it. Thanks for your trust.". [0]
[0] https://docs.cloud.google.com/storage/docs/storage-classes
^ Standard multi-region or dual-region storage has a 99.95% availability SLA, regional Standard has 99.9%, and regional Nearline, Coldline, or Archive can be as low as 99.0%. The credits are 10%, 25%, or 50% of the monthly bill for the affected service tier, with 50% as the aggregate monthly cap, applied to future use. Google also says the customer must request the credit within 30 days or forfeit it.
On top of this, there's a vast difference between "what do you mean that team spent $1000 on AI in their expense report, what did we get for that?" vs. "oh, the company-wide AWS bill went up by a few percent, let's look into that when we have time." The latter makes projects far more viable.
The security posture at AWS is different. AI startups are going to get hacked and leak data etc. All the startup webapp builder tools, vscode plugin players etc.
AWS could still be hacked, but they've taken some care to make it a bit less likely, a bit easier to track which customers affected etc. If you dig into AWS logging for example, there is a TON if you turn it on, you can really go back and see who did what to the permissions / environment etc. I imagine they've got pretty good logging of their staffs access to things as well. I had to jump through some hoops once to have their staff on my account.
Or to put it simply, nobody ever got fired for buying IBM.
I have just moved from a free environment in which I was able to use any AI harnesses or models to a strict enterprise environment.
I was shocked to realize how difficult it has been to have a GitHub CoPilot license on Azure. I mean, they're both Microsoft products. But no, the IT now has to figure out how to set up a GitHub enterprise, link to Azure subscription, and all that.
Yeah, cloud agents come with nice things like being able to filter content, implement guardrails like preventing PII or prompt injection from taking place. even if they sucked, at least liability wise you're set. I don't know how someone could even come close to this capability by doing it on their own. If anyone does, please share what tools, platforms and projects you're using.
while true, everyone signed this same data privacy agreement with anthropic / openai a long tiem ago
In my company is simpler, we deal with data under EU Export Control so we cannot use any US provider due to the CLOUD Act.
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.
To go a step further, the reason it's often impossible to add a new vendor if that you've signed a bunch of contracts with your customers saying you're not going to send their data to other vendors in all sorts of various flavors.
3. from my opportunity - For many (not all) LLMs, Bedrock gives you control over which country the data stays in. You have no control over that with the Claude API, for example. We do not work in the US and have strong requirements for the data to stay in our country, which Bedrock gives us control over.
A very interesting comment.
Curious to understand how AI will continue to grow if this is the trend. Assuming most valuable data is behind such firewalls. And whatever is public has been harvested, trained on top of whatever has been acquired illegally (this is a grey area).
Will it become a closed ecosystem without outside input?!
How is one certain bedrock data isn’t being shuttled to external providers?
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.
Wait, is AWS just reselling access to some AI company's servers, or is AWS running the models on their own hardware?
Even if you can get it approved you are adding surface area to your annual security audits, adding another vendor that needs to be disclosed on security assessments, spreading your data to yet another processor, and adding another invoice and budget discussion. Depending on your customer contracts you may need to notify them of a new vendor. This might trigger a new security review. Oh it’s just another model on Bedrock? Bliss.
Every CEO, board, and middle manager in the world is AI buzzword-obsessed now. Surely asking to sign a contract with the frontier labs directly would not get held up?
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.
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.
Claude is already available as both a pass-through to Anthropic's servers from AWS and in Bedrock. https://aws.amazon.com/claude-platform/ I imagine they're not thrilled that their first mover advantage has gone now, but they'll have seen it coming a mile off.
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.
It's so odd, because Claude models on Amazon Bedrock do support all those features.
For awhile now, I've had a api.anthropic.com emulator that "secretly" forwards requests to Amazon Bedrock. Works great and now I get all the nice first-party only features right away.
Auto mode works on Bedrock now!
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.
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 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.
was only a matter of time. enterprise teams on aws werent going to rearchitect their stack just for model access, easier to bring the models to where the workloads already are
FINALLY.
It's fascinating that cloud providers like AWS/GCP/Azure are now immovable "enterprise" technologies, in the way that IBM, Oracle, SAP, etc. were 15 years ago (and still are!).
Fond memories when only startups used S3 and EC2....
It's both an incredible triumph and tremendously sad that cloud providers are now the dinosaurs. So many companies are locked in, just as they were before. It's only going to get worse.
I wish the "cloud" was more fungible.
And the giant ai circle continues
One of the most attractive things a company can offer its engineers right now is a large token/compute budget.
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.
Are they? I don't see them in the Model Catalog on Bedrock.
Do they use Trainium/Inferentia?
But their contract with Microslop prevents this?!?!? They specifically said like a month ago that they wouldn’t sell API access on AWS, they would only release specific products.
Google 'openai azure contract dissolution'
any explanation of why the context window is only 272K?
Google apparently has custom chips that allow them to have the 1m context window.
No 5.5 Pro
More expensive than directly sourcing from OpenAI
The AWS pricing page says 10% more than OpenAI, which is probably because they’re forcing all inference through the US and data residency is at a 10% premium from the model vendors for whatever reason (because you’ll pay for it).
If they put in a global endpoint like with Claude (or OpenAI directly) then it’ll probably match the direct pricing, if the pattern holds.
(https://aws.amazon.com/bedrock/pricing/, scroll to OpenAI)
It's for people that can easily pump their AWS bill but not a new vendor.
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.
Their “junk bedrock equivalents” like opus?