Best app stack of 2026, according to LLMs: Next.js, Supabase, Vercel, Stripe

A test of 75 answers from ChatGPT, Claude, Gemini, Perplexity and Grok found that Next.js, Supabase, Vercel and Stripe were named together as the default app stack in 51 of 75 responses (68%), and in 42 of 45 answers when the engines were asked directly which stack to use. The same test found the engines rarely recommended their own makers' models: Gemini named OpenAI and Claude in all 3 AI-app answers and Gemini in none, Grok never named Grok, and only ChatGPT leaned home with OpenAI in 3 of 3. ChatGPT named an AI builder such as Lovable, Bolt, v0 or Cursor in just 1 of 15 answers, versus Gemini in 11 and Grok in 9.

The AI-Recommended App Stack, 2026: Every Engine Says Next.js, Supabase, Vercel and Stripe More and more apps start with a question to an AI: what should I build this with? We asked ChatGPT, Claude, Gemini, Perplexity and Grok 5 versions of it, 3 times each: 75 answers. They don’t give you a menu. They give you the same four products, and on the rest of the stack they disagree in ways worth knowing. Three Findings, Up Front - There is one default stack. Next.js, Supabase, Vercel and Stripe were named together in 51 of 75 answers 68% . Asked directly what stack to use, 42 of 45 answers named all four. - Engines barely push their own models. Asked what to build an AI app with, Gemini named OpenAI and Claude in all 3 answers and Gemini in none. Grok never named Grok. Only ChatGPT leaned home: OpenAI 3 of 3, Anthropic 1. - ChatGPT leaves out the AI builders. It named Lovable, Bolt, v0, Cursor or a similar tool in 1 of 15 answers. Gemini named one in 11, Grok in 9. The Stack Each Engine Would Build You For every layer of an app, the product each engine named most often, out of its 15 answers. Read across a row to see where the engines agree; read down a column for one engine’s whole stack. | Layer | Geminigemini-3.5-flash | Perplexitysonar | ChatGPTgpt-5.4-mini | Claudeclaude-haiku-4-5 | Grokgrok-4.3 | |---|---|---|---|---|---| | Framework | Next.js13/15 | Next.js10/15 | Next.js14/15 | Next.js11/15 | Next.js14/15 | | Database / backend | Supabase15/15 | Supabase12/15 | Supabase13/15 | Supabase13/15 | Supabase14/15 | | Hosting | Vercel15/15 | Vercel12/15 | Vercel13/15 | Vercel11/15 | Vercel12/15 | | Payments | Stripe / Lemon Squeezy12/15 | Stripe9/15 | Stripe13/15 | Stripe7/15 | Stripe12/15 | | Auth | Clerk8/15 | Clerk6/15 | Clerk8/15 | Auth03/15 | Clerk8/15 | | | Resend8/15 | Resend6/15 | Resend5/15 | Resend3/15 | Resend10/15 | | Analytics | PostHog5/15 | PostHog6/15 | PostHog7/15 | PostHog1/15 | PostHog10/15 | | Error monitoring | none named | Sentry3/15 | Sentry6/15 | Sentry3/15 | Sentry7/15 | | LLM API | Anthropic6/15 | none named | OpenAI5/15 | OpenAI4/15 | OpenAI / Anthropic6/15 | | AI builder / coding tool | Cursor11/15 | Cursor6/15 | FlutterFlow1/15 | Bubble / FlutterFlow4/15 | Cursor9/15 | The top four rows are close to unanimous. Supabase is the database in every column, and it is often the auth too: 25 answers say “Supabase Auth” in so many words, so the Auth row shows the dedicated services the engines name next to it. ChatGPT’s answer for a solo founder is the stack in one line: The Layers Below the Line The further down the stack, the thinner the consensus. Resend is the email default, as it was in our email API teardown https://openllmrank.io/blog/transactional-email-apis , but it was named in only 43% of answers to these open questions. Analytics and error monitoring are left out more often still: PostHog was named in 39% of answers Claude: 1 of 15 , Sentry in 25% Gemini: 0 . If you sell monitoring, the engines aren’t recommending against you. They mostly don’t get that far. Hosting has a long tail behind Vercel: Railway 17 answers , Cloudflare 14 , Fly.io 13 and Render about 11, counted by hand . Payments has one quirk: Gemini named Lemon Squeezy in 12 of its 15 answers, as the merchant of record that handles sales tax. ChatGPT, Claude and Perplexity named it in none of theirs. The LLM Layer: No Home Cooking We expected each engine to favour its own maker. It didn’t. On the question about building an AI app 3 answers per engine , these are the answers naming each model maker, counting model names like Claude and GPT-4o. ChatGPT tags the links in its answers with “utm source=openai”; we don’t count that as naming OpenAI. | Engine | OpenAI | Anthropic | | xAI | |---|---|---|---|---| | ChatGPT | 3/3 | 1/3 | 0/3 | 0/3 | | Claude | 3/3 | 3/3 | 0/3 | 0/3 | | Gemini | 3/3 | 3/3 | 0/3 | 0/3 | | Perplexity | 0/3 | 0/3 | 0/3 | 0/3 | | Grok | 3/3 | 3/3 | 1/3 | 0/3 | OpenAI and Anthropic are the default pair. Gemini, asked the question, recommended the competition: Note the model names. Of the 8 answers that named a specific model, 7 named a 2024-era one: GPT-4o, GPT-4o-mini, Claude 3.5 Sonnet. The engines recommend the right companies and the wrong versions, probably because many of the pages they read were written then. Perplexity named no model maker at all on this question. How You Build It Depends on Who You Ask Ask “what are the best ways to build an app” and the engines split. Gemini, Grok and Perplexity send you to AI builders and AI coding tools: ChatGPT almost never does 1 of 15 , and Claude names the older no-code tools instead 4 of 15 : Perplexity folds the AI tools straight into its stack: Who Wrote the Pages the Engines Read As in the email teardown, the most cited sites are vendors’ blogs, not documentation. appypie.com, an app builder, was cited in 9 answers. mindstudio.ai, an AI agent platform, in 7. makerkit.dev, which sells a Next.js and Supabase starter kit, in 11, including its own post on the 2026 SaaS stack. | Site the engines cited | Answers citing it | Times cited | |---|---|---| | appypie.com | 9/75 | 18 | | dev.to | 11/75 | 17 | | mindstudio.ai | 7/75 | 13 | | designrevision.com | 12/75 | 12 | | yle.fi | 3/75 | 12 | | makerkit.dev | 11/75 | 11 | | linkedin.com | 3/75 | 9 | | memeburn.com | 3/75 | 9 | | nextjs.org | 4/75 | 9 | | reddit.com | 3/75 | 9 | One caveat on this table: Perplexity returned 396 of the run’s 807 cited links, so it is mostly Perplexity’s reading list including a Finnish broadcaster’s topic pages, which have nothing to do with apps . ChatGPT cited only 28 links in all 15 answers, 9 of them on nextjs.org. Track what AI recommends in your category, every week This teardown is one snapshot of the app stack. AI answers differ by engine and shift as new pages get published. openllmrank re-asks your buyers’ questions across all five engines every week, with every answer and source, so you see when you or a competitor moves. Start tracking — $49/month https://openllmrank.io/wizard/brand Prefer a single snapshot? A one-time report is $79. What This Means If You Sell to Builders - Integrate with the default, don’t fight it. If 68% of answers start from Next.js, Supabase, Vercel and Stripe, the question builders ask next is “what works with that stack.” Have the page that answers it. - Starter kits write the stack. A boilerplate vendor’s post on the 2026 SaaS stack is a source the engines read. Being in the kits, and in their posts, puts you in the answer. - The lower layers are open. Analytics, monitoring and email are named in a minority of answers. Nobody owns them yet in AI answers, which makes them cheaper to win than the top four. - Check each engine on its own. Gemini’s Lemon Squeezy and ChatGPT’s silence on AI builders vanish in a blended number. Disclosure: openllmrank is built on the default stack in this post: Next.js, Supabase database and auth , Vercel hosting and Vercel Analytics and Stripe. It sends email through Postmark, calls the OpenAI, Anthropic, Google, Perplexity and xAI APIs, and sells the kind of AI-visibility measurement used in this post. Frequently Asked Questions What tech stack do AI engines recommend for building an app in 2026? Next.js, Supabase, Vercel and Stripe. Across 75 answers from ChatGPT, Claude, Gemini, Perplexity and Grok, Supabase was named in 89%, Vercel in 84%, Next.js in 83% and Stripe in 71%, and 51 answers named all four together. Resend email , Clerk auth and PostHog analytics were the most common add-ons. Do AI engines recommend their own maker's models? Not in this run. Asked what to use to build an AI app, Gemini named OpenAI and Anthropic models in all 3 of its answers and its own Gemini in none, and Grok never named Grok or xAI in any of its 15 answers. ChatGPT leaned closest to home: OpenAI in 3 of 3, Anthropic in 1. The samples are small, so read this as a direction, not a rate. Which AI engine recommends a different stack? They agree on the core stack, and split on how to build it. ChatGPT named an AI app builder or AI coding tool Lovable, Bolt, v0, Cursor and the like in 1 of its 15 answers; Gemini did in 11. Gemini was also the only engine to push Lemon Squeezy, in 12 of its 15 answers.