Business Chain tracks 100 programmes open to AI and machine learning companies, and the equity asked ranges from 0% to roughly 7.5% of the company. Founders fixate on that single percentage. The better question is what you get for it, because three different kinds of value get bundled into one term sheet line: cash, compute, and distribution. Price them separately before you sign anything.
Compute That Doesn't Touch Your Cap Table
The Together AI Startup Accelerator gives up to $15K in free platform credits at its Build tier, up to $30K at Scale, and up to $50K at its top Grow tier, with no equity attached to the credits themselves. For a company training or serving models, $50K in compute can outlast $50K in cash, because it doesn't show up as a liability and it doesn't dilute anyone.
The Google for Startups Accelerator: AI First Latin America runs the same logic. It's equity-free, eligible startups receive Google product credits, and there's an additional application path for further support beyond the base package. If you're building in Latin America, this is the only programme on our list that takes zero equity for compute, which makes it close to free money for anyone who clears the eligibility bar.
Data Access and Distribution: Snowflake and GSF
Snowflake for Startups offers up to $1 million in investments, but the number that matters more for an AI company is what sits behind it: placement inside Snowflake's data ecosystem and customer base. If your product consumes or enriches enterprise data, that access functions as distribution, not just capital, and it's worth weighing separately from the dollar figure.
The GSF Accelerator run by GSF India pairs seed investment with mentorship but publishes no fixed cheque size in its listing. Take that as a signal to ask directly before you count on a number. A programme that won't publish its terms up front is not automatically bad, but it does shift the burden of diligence onto you.
What the Straight Equity-for-Cash Deals Cost
- Conector Startup Accelerator: 4-7% equity for program plus services.
- gener8tor Investment Accelerator: $100,000 for 7.5% equity, rolling applications, no fixed deadline listed.
- Alchemist Accelerator: $25,000 stipend for roughly 5% equity, negotiable.
- Entrepreneurs Roundtable Accelerator: $150K on a 6% Post-Money SAFE, with W'27 and S'27 cohorts open.
- Katapult Accelerator: €150,000 to €500,000, though the organiser publishes no confirmed dates, so verify the cycle directly before you plan around it.
- Startup Wise Guys: roughly EUR 50,000 for 3-6% equity, no fixed deadline stated.
- Ben Franklin Technology Partners: $100,000 to $500,000.
- Virginia Venture Partners (CIT GAP Funds): up to $125,000 initial investment, with an October 30 application deadline at 12:00pm EST.
Line them up and the spread is stark. gener8tor's $100,000 costs 7.5% of the company. Virginia Venture Partners offers up to $125,000 at a lower implied dilution once you factor in their structure, and it comes with a hard deadline of October 30 at noon, which forces a decision instead of letting it drift. Katapult's range runs higher in absolute terms, €150,000 to €500,000, but without a published timeline you're negotiating blind on timing even if the cheque is larger.
Stack Credits Under One Equity Deal, Not Instead Of It
Credits programmes and equity programmes aren't competing for the same slot on your cap table, so stop treating them as alternatives. A founder can take Together AI's compute credits, up to $50K at the Grow tier, and still sign a $150K Post-Money SAFE with Entrepreneurs Roundtable Accelerator at 6%, because the credits don't touch the equity terms at all. The same goes for pairing Google's AI First LatAm product credits with a cash deal like Startup Wise Guys' roughly EUR 50,000 for 3-6%. The mistake is picking one programme and assuming it has to cover compute, cash, and distribution all at once. It doesn't have to, and for an AI company burning money on training and inference, it usually shouldn't.
If you only have room to negotiate one equity number this quarter, spend it on the programme that gives you something credits can't buy, which is distribution or a data relationship like Snowflake's. Then layer the equity-free compute programmes on top. That ordering gets you more total value for the same single slice of ownership than chasing the biggest headline cheque first.