The best AI for app development is the one that ships an app you can use, not a screen you can screenshot. We gave four frontier models two app briefs, a phone finance app and a team kanban board, one prompt each, and published what they built unedited. Every app below runs: send money, drag cards, undo, filter.
Which AI is best for app development?
Claude Opus 5.5 for the most finished app, GPT-6.1 Sol for the best value. On the finance app, every model completed the four-step send flow and updated the balance correctly, so the differences are craft, time and cost.
| Finance app | Time | API-equivalent cost | Notable |
|---|---|---|---|
| Claude Opus 5.5 | 69 min | $21.06 | Haptic feedback, balance sparkline, full-screen confirmation |
| Claude Fable 5.1 | 35 min | $11.46 | Animated balance, money in and out chips |
| GPT-6 Astra | 9 min | $2.73 | Numbered steps, airy layout |
| GPT-6.1 Sol | 14 min | $0.83 | Drawn status bar, slide-up review sheet |
Costs are what each build would have cost at the vendors' list API prices, from our run logs. Opus 5.5's figure covers only its successful attempt; three earlier attempts were interrupted, by an API outage, a usage limit and a stopped harness, and are listed on the build.
How did the AI handle a real interactive tool?
Well, and in a way a careful developer would recognise. The kanban boards implement drag and drop with pointer events, so it works with a finger as well as a mouse, show where a card will land, confirm each move with an undo option, save to the browser and open card details in a side panel. Each board was recorded dragging two cards across columns, undoing, filtering to Bug, opening a card and switching to dark mode, all without a hitch.
Can these apps go to production?
Not as they are. Each is a single front-end file with fixed data and no backend: no sign-in, no server, no real money. The value is in the speed of getting a working, well-designed prototype in front of users. For mobile specifically, they are web apps designed for a 390-pixel screen; an app-store release needs a native wrapper, and a finance product needs security review, for which OWASP's Mobile Application Security project is the usual starting point.
Which should you use for your app?
Choose by stage. Prototyping several ideas this week: GPT-6.1 Sol, because ten attempts cost less than one Claude build at list prices. Building the version you will show investors or users: Claude Opus 5.5, or Fable 5.1 for a calmer feel, and accept the hour. Either way, copy our finance app brief or kanban brief as a template: supply the data, list the flows step by step, and let the model design.
Four finance apps, names hidden. Tap through each, then reveal.
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Frequently asked questions
What is the best AI for app development?
For the most polished first build, Claude Opus 5.5; for a working app in about ten minutes at under a dollar of model time, GPT-6.1 Sol. All four models we tested built working apps from one prompt, so the choice is about polish, speed and cost.
Can AI build a mobile app?
It can build a mobile web app that behaves like a native one: every finance app here has a bottom tab bar, respects the phone's safe areas and completes a send-money flow. Publishing to an app store needs a native wrapper and backend that a single prompt does not provide.
How much does it cost to build an app with AI?
On subscriptions, it comes out of plan limits. At list API prices, our finance app cost $0.83 to build with GPT-6.1 Sol, $2.73 with GPT-6 Astra, $11.46 with Claude Fable 5.1 and $21.06 with Claude Opus 5.5.
Did the AI-built apps have bugs?
None logged a runtime error in our recordings, and every scripted interaction worked: the send flow, the balance update, dragging cards between columns, undo, filters and the details panel. Edge cases beyond the brief were not tested.