What is the best AI model for UI design in 2026?

It depends on the job. For hero-direction work where every detail matters: Claude Opus 4.7. For fast iteration on locked direction: Claude Sonnet 4.6. For cheap exploration, multi-variant generation, and early ideation: Gemini Flash. There is no single winner; the right tool is a model picker that lets you choose per generation. Locking yourself to one model means paying Opus credits for exploration work or accepting Flash quality for hero work.

Is Claude Opus 4.7 better than Sonnet 4.6 for UI design?

On a one-shot hero screen with restraint and atmospheric depth, Opus 4.7 produces visibly higher polish than Sonnet. The output reads more deliberately art-directed. The catch is cost: Opus runs on dMaya at roughly 220 credits per generation versus Sonnet at 110, and on Claude Pro one Opus generation can burn around 20% of a weekly limit. For iteration after the direction is locked, Sonnet is the right call. For the original direction-setting pass, Opus pays back.

Is Gemini Flash good for UI design?

For exploration, yes. Gemini Flash is fast, cheap, and willing to commit to bold structural choices that Opus and Sonnet sometimes hedge on. We use it specifically for generating wide variations early in the design phase: same brief, five different aesthetic directions, see which one the client reacts to. For the final shipped design, Flash output usually needs Opus or Sonnet to refine. Treat Flash as the option-generator, not the deliverable.

What about Gemini Pro for UI design?

Gemini Pro produces noticeably more polished output than Flash on UI tasks. We run Gemini Pro through Stitch (Google's Stitch 2.0 uses Gemini 2.5 Pro). On the same brief Stitch on Pro takes about two minutes and produces output similar in quality to Flash on dMaya, with the rough positioning issues Stitch is known for. Pro inside a tool that handles multi-screen consistency better is more useful than Pro inside Stitch. Worth watching as Gemini Pro becomes more available across vibe design tools.

How much does each model cost in real workflow?

Inside dMaya: Opus 4.7 runs at roughly 220 credits per generation, Sonnet 4.6 at 110, Gemini Flash at the cheapest tier. Inside Claude Pro for Claude Code or Claude Design: Opus consumes about 20% of a 5-hour usage window per heavy generation, Sonnet roughly half that. Inside Stitch: Gemini Flash and Pro are both free during Labs, capped at 350 generations per month on Standard. The real-cost differences become large fast: a hundred Opus generations can equal a thousand Flash generations on credit basis.

Which model has the best multi-screen consistency?

None of them solve multi-screen consistency at the model level. Consistency is a tool problem, not a model problem. Each generation is independent at the model layer; the canvas is what carries shared state across screens. dMaya's persistent canvas does this regardless of which model you pick per generation. Stitch and Claude Design produce one screen at a time. Pick a model based on quality and cost trade-offs, then pick a tool that handles multi-screen consistency separately.

Should I use a tool that lets me pick the model, or a tool that picks for me?

Pick the tool that lets you pick the model, every time. The cost difference between Opus and Flash is large enough that being locked to one model means systematically over-paying or under-quality-ing. Tools with a model picker (dMaya is currently the most explicit) let you match model to job. Claude Design locks you to Opus 4.7. Stitch locks you to Gemini Flash or Pro. Figma Make uses Claude under the hood with no user control. The locked tools work for their narrow use case; for everything else, the model picker pattern is the right default.

Does Claude Opus 4.7 actually beat GPT-4o or Gemini Pro on UI design?

On UI design specifically, our hands-on testing across the same brief favors Claude Opus 4.7 for output that requires restraint and craft (typography commitment, tasteful color, atmospheric depth, considered spacing). Gemini Pro gets close but Stitch's framing limits the output. GPT-4o we have not tested directly inside a vibe design tool. The benchmarks on UI design tasks are still informal and tool-dependent. Until someone publishes a clean cross-model UI benchmark, the honest answer is that Opus is the strongest of the models we have tested directly on the same brief.

Which model is the cheapest for UI design?

Gemini Flash is the cheapest both in absolute terms and per-design-iteration. Inside dMaya it runs at the lowest credit cost. Inside Stitch, Flash and Pro are both free during Labs. The trade-off is quality: Flash produces output that needs more cleanup before it is client-ready. For solo work and exploration, Flash is the right cost-quality compromise. For deliverable work, the credit difference is worth paying for Sonnet or Opus.

What is the model picker pattern?

A user-facing UI control that lets you choose which AI model runs each generation. dMaya is the most explicit implementation in the vibe design category: a dropdown that includes Opus, Sonnet, Gemini Flash, and others, switchable per generation without restarting the session. The pattern matters because cost and quality differences across models are large, and locking the entire workflow to one model means systematically suboptimizing one of those axes. Other tools will likely add the pattern over the next year.

AI Models · 2026 Hands-On Test

The Best AI Model for UI Design in 2026: Claude Opus vs Sonnet vs Gemini Flash, Tested

Dhairya Purohit

Builds dMaya. Ships AI design workflows in real client work.

Published April 29, 2026

Most AI design tools lock you to one model. Claude Design runs Opus 4.7. Stitch runs Gemini. Figma Make uses Claude under the hood without telling you which version. The cost and quality differences across models for UI design work are large enough that the locked-tool pattern leaves real money and real polish on the table.

We ran the same UI brief through Claude Opus 4.7, Claude Sonnet 4.6, and Gemini Flash inside dMaya, where the model picker is a per-generation choice. Same prompt, same evaluator, same hour. This is the test write-up: which model wins for which job, what each actually costs, and the case for picking the model per generation instead of accepting whatever a tool decided for you.

We are dMaya. The model picker is one of the things that distinguishes us from the locked-tool alternatives. The numbers below are real. Use them to pick the right tool for your work, even if that ends up not being us.

Why model choice matters more than tool choice

For UI design specifically, the model is doing the visual judgment work. The tool is the canvas around it. Different models produce noticeably different output on the same brief, and the cost spread across models is a 5x to 10x range depending on plan and provider.

Concrete: a hundred Opus 4.7 generations on Claude Pro can burn a full week of usage. The same hundred generations on Gemini Flash inside Stitch is free during Labs. The same hundred on Sonnet 4.6 in dMaya is roughly half the credit cost of Opus. None of these are small differences, and they compound across an agency running multiple client projects.

The honest answer to "what is the best AI model for UI design" is that it depends on what you are about to do in the next 30 seconds. Hero direction setting is a different job from variant exploration is a different job from final iteration. Different jobs want different models.

The test setup

Same brief across all three models, run inside dMaya so the canvas, tooling, and prompt plumbing were identical. Tested on April 24, 2026. The brief: a freelancer SaaS dashboard, editorial typography, restrained palette, atmospheric depth on the hero only, four screens.

Each model got one shot, no priming, no follow-up corrections. Output graded on output quality (polish), structural correctness (positioning, spacing), and consistency across screens. Timer started on submit, stopped when generation completed. Credit cost recorded.

We did not test against models in their native locked tools (Claude Design's Opus, Stitch's Gemini). Those comparisons live in the three-tool comparison. This test is about the model itself, with the tool variable held constant.

Claude Opus 4.7: hero direction

Claude Opus 4.7 inside dMaya on the test brief. ~2.5 minutes, ~220 credits, multi-screen output.

Opus 4.7 produced the most deliberately art-directed output of the three. Typography committed to a serif-display + sans-body pairing. Restraint in the palette: two colors plus a soft accent. Atmospheric depth used only on the hero, exactly as briefed. Spacing rhythm consistent across the four screens. The output looked like a designer made it.

Time: roughly 2.5 minutes from submit. Credit cost: about 220 credits in dMaya, or approximately 20% of a 5-hour Claude Pro window if run via Claude Design. Output usable as client-ready first pass with light cleanup.

When Opus wins:hero pages, pitch decks, the moment in a project where every detail matters and you are setting the direction. Not for fast iteration; the cost per generation makes it the wrong choice for "move that 16px to the right" work.

Claude Sonnet 4.6: fast iteration

Claude Sonnet 4.6 inside dMaya on the test brief. Faster than Opus, half the credit cost.

Sonnet 4.6 produced output close to Opus on structural correctness and palette commitment, with slightly less polish in the typographic and spacing details. Most readers would not notice the gap on a single screen; the difference shows up in the small decisions Opus makes more deliberately (font pairing, kerning, atmospheric layering on the hero).

Time: faster than Opus on the same brief. Credit cost: about 110 credits in dMaya, roughly half of Opus. Output usable as a strong iteration pass once direction is set.

When Sonnet wins: the iteration phase after the hero direction is locked. Cosmetic refinements, additional screens that need to match an established visual language, fast adjustments where Opus would be over-spec. The right default for most generations after the first one.

Gemini Flash: cheap exploration

Gemini Flash inside dMaya on the test brief. Fast, cheap, willing to commit to bold structural choices.

Gemini Flash produced output that was structurally bolder than Sonnet but with less restraint. Where Opus and Sonnet hedged on a typography choice, Flash committed. Sometimes that commitment landed (a striking layout we would not have prompted toward). Sometimes it overshot (motion or color choices that needed refinement).

Time: fastest of the three. Credit cost: cheapest tier in dMaya. Output usable as a first-pass for variant exploration; usually needs a follow-up generation in Sonnet or Opus to refine for delivery.

When Flash wins: exploration. Generate five variants of the same brief on Flash to see what aesthetic territories exist before committing. Flash is also useful for non-precious work like internal admin dashboards where the cost-quality trade-off favors speed.

Side-by-side comparison

Metric	Opus 4.7	Sonnet 4.6	Gemini Flash
Time to output	~2.5 min	faster than Opus	fastest
Credits / generation (dMaya)	~220	~110	cheapest tier
Output polish	Highest	High	Bold but less restraint
Restraint / nuance	Strong	Strong	Lower
Best use	Hero direction, pitch decks	Iteration, additional screens	Exploration, variants
Worst use	Cosmetic tweaks (over-spec)	Wide aesthetic exploration	Final client deliverable

The numbers are honest. The ranking is not absolute. The right model is the one that fits the next 30 seconds of work.

Pick the model per generation, not per session.

dMaya's model picker lets you choose Opus, Sonnet, or Gemini Flash on each generation. Plans start at $18/mo.

Start Designing

Decision tree: which model when

Use Opus 4.7 when

✓ Setting the hero direction for a project
✓ Pitch deck or client-facing showcase
✓ Output needs to be art-directed, not just functional
✓ One pass should be close to deliverable

Use Sonnet 4.6 when

✓ Direction is locked, you are iterating
✓ Generating additional screens for an existing language
✓ Cost matters and you cannot justify Opus
✓ Default for most generations after the first

Use Gemini Flash when

✓ Exploring aesthetic territory before committing
✓ Generating multiple variants for review
✓ Internal tools where speed beats polish
✓ Cost-sensitive work or hobby projects

Why the model picker pattern wins

Locked-model tools work for the narrow case where one model fits all the work you do. Claude Design fits a designer who only ever needs Opus output and is happy paying Pro weekly limits for it. Stitch fits a hobbyist who only ever needs Flash exploration and does not care about polish. For everyone else, the lock is a tax.

The picker pattern matches the reality that a single project pulls work from across the cost-quality curve. Hero direction wants Opus once. Iteration wants Sonnet five times. Variant exploration wants Flash twice. A picker lets you spend the right credits on each of those steps without restarting the session or switching tools.

dMaya is currently the most explicit implementation in the vibe design category. Other tools will likely add the pattern over the next year because users will not accept paying Opus rates for variant exploration once they have seen the alternative.

For the broader picture on how vibe design tools differ on the model question and on everything else, see our vibe design field guide and the three-tool comparison with full timings.