Which startup program gives the most cloud credits in 2026?

Google for Startups currently publishes the highest ceiling: up to 200,000 dollars over two years for funded startups and up to 350,000 dollars for AI-first startups. AWS Activate Portfolio reaches roughly 100,000 dollars, and Microsoft for Startups tops out around 100,000 to 150,000 dollars via an Investor Network referral. Tiers change, so check current terms before applying.

Can I apply to AWS Activate, Google for Startups, and Microsoft for Startups at the same time?

Yes. The three programs do not exclude each other, and stacking them is normal. Most teams claim Microsoft's self-serve tiers first, file AWS Activate on the Founders or Portfolio path, and apply to Google once they have equity funding or a strong AI-first case.

Which cloud startup program is best for bootstrapped founders?

Microsoft for Startups. Its ladder starts at 1,000 dollars on signup and reaches 5,000 dollars after business verification with no investor required. AWS Activate Founders is also self-serve but smaller, and Google's pre-funding tier is around 2,000 dollars.

Which program is best for AI startups?

It depends on your model stack. Building on GPT models points to Microsoft and Azure OpenAI. Gemini-based products fit Google, whose AI-first tier is also the largest published credit package. AWS Bedrock covers the widest menu, including Claude, Llama, and Mistral, if you want multi-model optionality.

Do these startup cloud credits expire?

Yes, all of them. AWS credits typically lapse within months to a couple of years of issue, Google structures its big tiers over two years with partial coverage in year two, and Microsoft's top tier draws down over up to five years. Apply when you are ready to deploy so the clock does not run while you build.

AWS Activate vs Google for Startups vs Microsoft for Startups (2026)

AWS Activate vs Google for Startups vs Microsoft for Startups in 2026: credit amounts, tiers, AI model coverage, expiry, and lock-in compared side by side.

Short answer: if you are an AI-first startup with any equity funding, Google for Startups currently publishes the largest number, up to 350,000 dollars in credits for its AI tier. If you are bootstrapped and want the biggest instant grant, Microsoft for Startups is the friendliest, with a self-serve path that scales from 1,000 to 5,000 dollars without an investor. AWS Activate sits in the middle on headline size (up to roughly 100,000 dollars via the Portfolio path) but wins on ecosystem breadth and the sheer number of accelerators and VCs that can unlock it. And here is the part most founders miss: these programs do not exclude each other. You can, and usually should, apply to all three.

That said, one of them will end up being your primary cloud, and that choice matters more than the credit number. Below is how the three programs compare in 2026 on the axes that actually decide it: amounts, tiers, AI coverage, expiry, lock-in, and how painful the application is. Published tiers shift over time, so treat the figures here as the current shape of each program and check the live entries in the catalog before you apply.

The comparison at a glance

	AWS Activate	Google for Startups Cloud	Microsoft for Startups
Self-serve tier	Founders path, small starter grant	Around 2,000 dollars for pre-funding startups	1,000 dollars at signup, 5,000 after verification
Top tier	Up to ~100,000 dollars (Portfolio)	Up to 200,000 dollars over 2 years; up to 350,000 for AI-first	Up to 100,000 to 150,000 dollars via investor referral
Unlock for top tier	Activate Provider Org ID from an enrolled VC or accelerator	Equity funding; AI-first status for the biggest tier	Referral from the Microsoft for Startups Investor Network
AI model access	Bedrock (Claude, Llama, Mistral, Amazon Nova)	Vertex AI and Gemini	Azure OpenAI (GPT models) plus Azure AI Foundry
Typical credit window	Months to about 2 years from issue	Structured over 2 years (year 2 is partial coverage)	Drawn down over up to 5 years on the top tier
Extras	AWS support credits, ecosystem discounts	Enhanced support credits, startup success resources	GitHub Enterprise, Microsoft 365, developer tooling

Amounts and tiers: who actually pays out the most

The headline numbers hide a two-track reality that all three programs share. There is a small self-serve tier anyone with a real product can get, and a large partner tier that requires someone else to vouch for you.

AWS Activate splits into Founders (self-serve, small) and Portfolio (up to roughly 100,000 dollars, unlocked by a partner Org ID from an enrolled VC or accelerator). The full mechanics are in our AWS Activate guide.
Google for Startups offers around 2,000 dollars pre-funding, then jumps hard once you have equity backing: up to 200,000 dollars over two years for the standard track, and up to 350,000 dollars for AI-first startups. Year one is fully covered up to a cap; year two covers only a percentage of spend. Details in our Google for Startups guide.
Microsoft for Startups runs a laddered model: 1,000 dollars to start, 5,000 after verifying your business, and 100,000 to 150,000 dollars with a referral code from the Investor Network. The middle rungs are the most accessible of the three programs for bootstrapped teams. Our Microsoft for Startups guide walks the ladder.

So the ranking depends on who you are. Funded AI startup: Google publishes the biggest ceiling. Bootstrapped: Microsoft gives you the most without an investor. Accelerator-backed: AWS is the most widely wired into accelerator batches, so the Portfolio unlock is often just an email to your program manager.

AI and model coverage: the axis that decides it in 2026

If your product is built on foundation models, the real question is not the credit amount, it is which models your credits can buy.

Azure is the home of the OpenAI API in cloud form. If you are building on GPT models and want your inference covered by startup credits, Microsoft is the direct route, and the Azure OpenAI allowance is the quiet crown jewel of the top tier.
Google routes everything through Vertex AI and Gemini. Gemini models are aggressively priced (our rankings track the cheapest verified endpoint per model weekly, and Gemini variants regularly top the value charts), so Google credits stretch far on inference.
AWS Bedrock is the multi-model play: Claude, Llama, Mistral, and Amazon's own Nova models under one billing surface. If you want optionality across model families rather than a bet on one lab, Activate credits cover the widest menu.

The pattern: pick the cloud whose model catalog matches your stack, because burning six figures of credit on a cloud whose models you do not use is just deferred migration pain.

Expiry and lock-in: read this before you celebrate

Credits are a loan of attention. Each program structures the clock differently.

AWS credits carry an expiry window commonly measured in months to a couple of years, and unused credit lapses. Apply when you are ready to deploy, not the day you incorporate.
Google structures the big tiers over two years, with year two covering only part of your bill. That step-down is deliberate: by year two you have real spend habits on GCP.
Microsoft spreads the top tier over as long as five years, which is genuinely founder-friendly pacing, but the bundled tooling (GitHub Enterprise, Microsoft 365) is designed to make your whole company Microsoft-shaped.

Lock-in is the actual product these programs sell. None of it is sinister, but plan for the day the credits end: keep your infrastructure portable where cheap (containers, standard Postgres, S3-compatible storage) and accept lock-in only where the managed service is truly better.

Application friction

Microsoft: lowest friction at the bottom. The first two tiers are self-serve with light verification.
AWS: Founders path is a short form; Portfolio is trivial if your accelerator or VC is enrolled and impossible if not.
Google: the small tier is easy; the six-figure tiers involve funding verification and, for the AI tier, an assessment of whether you are genuinely AI-first.

The stacking play

Since none of these programs disqualify you from the others, the optimal move for most teams is: claim the Microsoft self-serve tiers today, file AWS Activate on whichever path you qualify for, and apply to Google the moment you have equity funding or a credible AI-first story. Then run your primary workload on the cloud that matches your model stack, and keep the others as burst capacity or negotiating leverage. Our startup credits checklist sequences all of this alongside the AI API programs and the SaaS long tail.

Bottom line

There is no single winner. Google pays the most if you are funded and AI-first. Microsoft is the best deal for bootstrappers and GPT-based products. AWS has the broadest model menu and the deepest accelerator wiring. Apply to all three, spend primarily on one, and time your applications to when you can actually burn the credit, because every program's clock starts at approval, not at your launch.

Perkstack tracks all three programs, plus 200 or more other verified credits and perks, with apply links, difficulty ratings, and re-checked terms. Browse the catalog or create an account to work through them systematically; membership pays for itself with the first mid-size credit you claim.