Search for the best text-to-UI generator and you will find a dozen rankings. Almost every one is published by a company selling a text-to-UI generator, and almost every one puts its own product at number one.
We do not sell any of these tools. Fivecube is a product design agency, and our designers use AI generators in real client work, mostly for early exploration. This guide compares ten of the most used tools by what they actually produce, then covers what we saw when we tested three of them hands-on, where they still fall short, and how to write prompts that give you something usable.
AI is already part of most design workflows. In Figma's 2025 State of AI in Design report, 89% of designers said they use AI to improve their process, though only about a quarter used it to generate UI components. That gap says a lot about where these tools are today.
What Is a Text-to-UI Generator?
A text-to-UI generator is an AI tool that turns a written description of a screen or app into an interface design. You describe what you need, such as "a mobile login screen with email, password and Google sign-in," and the tool produces a layout with components, styling and sometimes working front-end code. Most tools also accept screenshots, sketches or URLs as input.
The output varies a lot. Some tools give you an editable mockup, some paste layers into Figma, and some generate React code you can deploy. That difference matters more than any ranking, so the comparison below is grouped by output.
Best Text-to-UI Generators at a Glance
Prices are entry-level paid plans as listed in October 2026, billed annually where that option exists. Nearly all of these tools meter usage in credits or tokens, so the real monthly cost depends on how much you generate.
Tool | What you get | Best for | Free plan | Paid from |
|---|---|---|---|---|
Google Stitch | Mockups, Figma paste, HTML/CSS | Free exploration of web and mobile screens | Yes, with usage limits | No paid plan yet |
Uizard | Editable mockups and prototypes | Quick wireframes for non-designers | Yes, limited generations | $12/mo |
Visily | Editable mockups, diagrams | Teams turning screenshots and sketches into wireframes | Yes | $11/editor/mo |
UX Pilot | Screens, Figma plugin, code | Designers who want AI inside Figma | Yes, one-time credits | $14/mo |
Banani | Multi-screen designs, Figma export | Product managers mapping flows | Yes | $12/mo |
Figma Make | Interactive prototypes and code inside Figma | Teams already working in Figma | Yes, 500 AI credits/mo | $16/seat/mo (Figma Professional) |
v0 by Vercel | React and Next.js code | Developers building front ends | Yes, small monthly credit | $30/user/mo |
Lovable | Full-stack web apps | Founders building an MVP without code | Yes, daily credits | $21/mo |
Bolt.new | Full-stack web apps in the browser | Developers prototyping fast | Yes, monthly tokens | $25/mo |
Framer AI | Live, responsive websites | Marketing sites and landing pages | Yes | $10/site/mo |
One tool you may still see in older lists is Motiff. It has been discontinued. Galileo AI, another familiar name, is now Google Stitch.
From Prompt to a Product People Use
AI gets you a first draft. We turn it into an interface that fits your brand, your users and your design system.
Text-to-UI Tools by What They Produce
How Much Text-to-UI Tools Really Cost
The sticker prices in the table look small, and for light use they are. The catch is metering. Almost every tool here sells credits or tokens, and one prompt does not cost one credit.
In Figma Make, a single request can use anywhere from about 30 to over 100 credits, and generating an app from scratch sits at the high end. A Professional seat comes with 3,000 credits a month that do not roll over. v0 and Bolt bill by tokens, so a long conversation with many revisions costs far more than one clean prompt. Lovable charges less for a small style change than for building a whole page.
Prices also move fast. v0 retired its old $20 plan for new users, Stitch is free today with no promise it will stay that way, and several tools changed their credit rules more than once this year. Before paying, run one realistic task on the free tier, such as three or four connected screens with a revision round, and see how many credits it actually burns. That number tells you more than any pricing page.
What We Found Testing Figma Make, Stitch and Uizard
Our designers tested three tools on the same kind of brief: real screens for a real product type, with specific instructions on layout, color and spacing. The rest of the tools in this guide are described from public documentation and pricing, not from our own testing.
Tool | What worked | What didn't |
|---|---|---|
Figma Make | Fast, clean edits through prompts; adding basic interactions saved real time | Output worked as a springboard and needed rework; AI-generated images were weak; interactions held up only for simple flows |
Google Stitch | Chat-based editing; several variations per prompt; Figma and HTML/CSS export | Inconsistent results; generic visuals; messy layer structure after Figma export |
Uizard | Brand kit upload; clean output; easy to learn | Simplistic layouts; hard to meet accessibility standards; a 300-character prompt limit in Autodesigner at the time of testing; limited layer detail |
The pattern was the same across all three. A first draft arrived in a few minutes, and it was a reasonable starting point. Getting from that draft to something we would show a client took the usual design work.
Stitch was the clearest example of a problem we saw everywhere: it sometimes ignored explicit instructions on color and spacing, even when the prompt spelled them out. None of the three tools could work against an existing design system such as Material Design, so every component had to be checked by hand.
Where Text-to-UI Generators Work Well
Speed is the obvious one. A low-fidelity prototype that used to take an afternoon can now take a few minutes, which changes how many directions a team is willing to explore before committing.
They also reward precision. A vague prompt like "a dashboard for a fitness app" returns something generic. A prompt that lists the components, the data each card shows and the actions available gets surprisingly close to a custom layout, and code-first tools will produce front-end code to match.
And they are good at first drafts. Treating the output as a draft, not a deliverable, is what makes these tools useful. A rough layout on the screen is easier to react to than a blank canvas, especially in a workshop with stakeholders who do not think in wireframes.
Where They Still Fall Short
Generic output
Generators learn from common patterns, so their screens look like common patterns. Cards, a sidebar, a hero with a gradient. For an internal tool that is fine. For a product that needs to stand apart from competitors, it is a starting point at best.
No real context
A prompt cannot carry everything a designer knows about the product: the brand, the existing app, the audience, the regulations, the business goal behind each screen. When we designed HYCM's mobile investment app, the hard decisions were about how traders read risk and act under time pressure. No generator could have made those calls from a text box.
Inconsistency and design system drift
Ask for five screens and you often get five slightly different button styles, spacing scales and type sizes. None of the tools we tested respected an existing component library, which means generated screens break consistency the moment they meet a real product. If your team relies on a design system, expect to rebuild generated screens with your own components.
Accessibility
Contrast, focus order, touch target sizes and screen reader labels are rarely handled well by default. Uizard in particular made it hard to meet accessibility standards in our test. Generated UI needs an accessibility pass before it goes anywhere near production.
How to Write Prompts That Produce Usable UI
Most poor results come from prompts that describe a feeling instead of a screen. These habits made the biggest difference for us:
Start with the user and the goal of the screen, for example "a returning customer checking the status of an order," before naming any components.
List the components and the data in each one: "a header with the order number, a progress tracker with four steps, a list of items with thumbnails and prices."
Name the platform and size, such as iOS mobile, desktop web at 1440 pixels, or a tablet dashboard, so the layout logic fits.
Give hard constraints with exact values: brand colors as hex codes, the font family, corner radius, and whether you want light or dark mode.
Work one screen at a time, then ask for states: empty, loading, error and success versions of the same screen.
Attaching a screenshot of your existing product or a reference you like usually beats a paragraph of adjectives. Most tools now accept images, and the results stay much closer to your visual language.
How to Choose a Text-to-UI Generator
Start with what happens to the output next. If a designer will refine it in Figma, pick a tool with clean Figma export or one that works inside Figma, like UX Pilot or Figma Make. If a developer will build from it, a code-first tool like v0 saves a translation step. If nobody will touch it after you, and you just need a working app to test an idea, Lovable or Bolt make more sense.
Then look at who will use it. Uizard and Visily are built for people without design training, which is great for founders and product managers and limiting for designers who want control over every layer. UX Pilot and Figma Make assume you already know your way around a design file.
Check how the tool handles your brand. Some let you upload a brand kit or reference screenshots; others mostly ignore style instructions. Ask it for a screen in your colors and fonts on the free plan and see how close it gets.
Finally, think about the layer structure. A screen that looks right but exports as a pile of ungrouped shapes costs more time to fix than to redraw. Export one result to Figma and open the layers panel before you commit.
When to Use a Generator and When to Bring In a Designer
Text-to-UI tools earn their place early. They are useful for brainstorming before you hire anyone, for turning a rough idea into something you can show investors or teammates, for generating several directions quickly, and for speeding up wireframes. If you are deciding between a quick proof of concept and a fuller build, our guide to PoC vs. prototype vs. MVP helps frame how much design each stage really needs.
They are not ready to replace product design for anything customers will rely on. Complex flows, custom interactions, products in regulated industries and anything that has to scale across dozens of screens still need someone who can test with real users, make trade-offs and keep the system consistent. That is the point where a generated draft should move to a designer, not to production.
By
Fivecube Team
Frequently Asked Questions
Which AI tool is best for UI design?
It depends on the output you need. Google Stitch is the strongest free option for mockups, Figma Make suits teams already in Figma, v0 is best for React code, and Lovable or Bolt fit founders who want a working app.
Can AI create UI design?
Yes, AI can generate layouts, components and even working front-end code from a text prompt. The results are good first drafts but usually need a designer to fix consistency, accessibility and brand fit.
Is there a free text-to-UI generator?
Google Stitch is free with daily usage limits. Uizard, Visily, UX Pilot, Banani, Figma, v0, Lovable and Bolt all offer free plans with limited credits.
How do you use AI as a UI designer?
Most designers use it for exploration: generating layout options, filling screens with realistic content and producing quick prototypes for early feedback. The final design is still built and refined by hand in a tool like Figma.
Is AI replacing UI/UX designers?
No. AI speeds up drafts, but it cannot research users, weigh business trade-offs or keep a growing product consistent. Those parts of the job are becoming more important, not less.
Is UI/UX still in demand in 2026?
Yes. AI has taken over some routine production work, but companies still need people who can decide what to build and make it usable. Demand has shifted toward designers who combine research, systems thinking and comfort with AI tools.
Text-to-UI generators are worth using, as long as you know what you are getting: a fast, generic first draft. Pick a tool by the output you need, write prompts like a brief, and plan for the design work that turns a generated screen into a product people trust.
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