Pokémon bakeoff reveals best JavaScript frameworks for AI

A recent "PokéAPI bakeoff" showcased how JavaScript frameworks' performance varies when AI agents are tasked with building web applications. Software developer Nolan Lawson, at AI security firm Socket, aimed to eliminate bias in framework selection for AI tasks. Lawton's experiment pitted 12 JavaScript frameworks against Claude Code, an AI model, to build a basic Pokémon web application following the same setup 12 times.

Using tools like Hono, htmx, Astro, and Nuxt, Lawson gauged each framework's build cost, maintainability, and end-user performance. Server-centric frameworks like Hono and htmx performed best, with a median cost of $2.67 per app and fastest build time. Astro and Nuxt were close runners-up, favoring server-side data processing and reduced boilerplate.

Traditional frameworks like Angular and SvelteKit lagged behind, consuming more tokens and taking longer to execute. While AI can streamline framework selection, developers worry about the long-term maintenance and reviewability of their codebase.