supersonic insights

The battle of AI design tools

Figma Design, Figma Make and Claude Design, benchmarked against a real production codebase

Three AI design tools, one real question: which one actually earns its place in a production codebase? We put Figma Design, Figma Make and Claude Design head to head and scored each one against five criteria: efficiency, token usage, accuracy, code quality and consistency. This wasn't a documentation comparison. It was hands-on, implementing real components with each tool and measuring what came out the other end.

hree floating design panels with abstract steel-blue wireframe layers, the central panel forward and outlined in green
Author
Headshot of Jorge Barassa, Software developer at supersonic

Jorge Barrasa

Publishing date

Sep 28, 2026

Designer seen from behind at a cockpit console with a floating design canvas of layered wireframe panels and a green selection marker

Testing for the real world, not the tool's comfort zone

Tested on Blackbird's actual stack, not each tool's default

Most AI design tool comparisons test a tool on its own terms: whatever framework it prefers, whatever output it's optimized for. We didn't do that. Our accelerator store Blackbird, which we used to conduct the tests, runs on NuxtJS, Vue, TypeScript and Bulma, and two of the three tools we tested default to generating React and Tailwind instead.

Rather than score them on that friendlier home turf, we measured the full cost of getting each tool's output into Blackbird's actual codebase, conversion included. It's a harder test to pass, and it's exactly the kind of test that separates a tool that looks good in a demo from one that holds up on a real project.

One more condition shaped the results just as much as the stack: this was a test of redesigning existing Blackbird components, not building new ones from scratch. It might thus lead to different results than we'd find for greenfield prototyping.

Since the tools evolve fast, it's worth noting the tests were carried out in Q3 2026.

Blackbird product detail page with color selection, subscription option and stock status

Blackbird homepage met categorienavigatie en uitgelichte producten, gebouwd op de echte productiecodebase

Overview of Blackbird UI components: dropdown menus and modals for cart, account and address management

The three approaches, and how we scored them

Tested side by side against the same criteria

We evaluated Figma Design (through Figma's MCP integration, implemented via Claude Code with a purpose-built skill), Figma Make (Figma's own AI generation tool), and Claude Design (Claude's native design-to-code rendering).

On efficiency, all three were fast to get an initial result out. The real time cost sat in testing and verifying that result against the design, not in generating it. Figma Design needed the least follow-up verification of the three.

The numbers on token usage were decisive. Figma Design landed at 20 to 40 thousand tokens per component implementation, Figma Make at 40 to 60 thousand, and Claude Design at 60 to 100 thousand. Accuracy followed a similar pattern: Figma Design and Figma Make both reached a near 1:1 match with the source design within one to two prompts, while Claude Design typically needed two to four prompts to get there.

Code quality came out even across all three, each tool consistently followed Blackbird's existing conventions and added comments where a change was substantial enough to warrant explaining. None of the three produced code the team couldn't maintain.

Consistency depended heavily on component size. Figma Make stayed reliable across repeated runs when components were tested individually, and Figma Design showed the same pattern: less consistent on large components, but just as reliable once broken into smaller pieces. Claude Design didn't follow that pattern, it stayed inconsistent even at the component level.

Why Figma Design won

Reading structure and tokens straight from the source file instead of reinterpreting the design

All three tools produced maintainable code that stuck to existing project conventions reasonably well. But they all shared the same tax: none of them natively speaks Vue and Bulma, so every option required some conversion from its default output. What set Figma Design apart wasn't dodging that effort, but reading structure and design tokens directly from the source file rather than generating a fresh interpretation of the design. That gave the team less to convert and less to double-check, which is why it still came out most token efficient and most accurate.

One thing shapes this whole comparison: Blackbird's use case here is redesigning existing components, not building from a blank page. Figma Make is built for turning a design into a new, working prototype. A real strength when there's no existing codebase to fit into. Starting a project from scratch, it would likely be the better pick. On a redesign, where the job is matching something that already exists rather than inventing something new, that same strength turns into overhead, and that's a real part of why it lost here.

This led us to take the decision to standardize on Figma Design as the source of truth for Blackbird UI work, implemented through Claude Code with a purpose-built skill. AI design tools are moving fast, and this comparison is a snapshot (Q3 2026), not a permanent verdict. supersonic will keep re-testing as Figma Design, Figma Make, Claude Design and any other relevant tools evolve, so we can keep providing valuable recommendations.

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What this means if you're evaluating the same thing

Your stack, your test

Test against your actual stack, not the tool's default output, even when that makes the test harder to run. Smaller components consistently outperformed larger ones across all three tools, so breaking work down pays off regardless of which tool you pick. A hands-on evaluation like this one will allow for more confident decision-making.

Questions about how this applies to your own project, or want to talk it through with us directly? Supersonic is happy to help.

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