Type a description, get a UI. That's the promise. The reality is more nuanced. After testing every major text-to-UI tool on the market, here's what actually works, what's marketing fluff, and where each tool fits.
Quick Overview
| Tool | Pricing | Output | Best For |
|---|---|---|---|
| v0 by Vercel | Free / $20-100/mo | React + Tailwind | Next.js developers |
| Galileo AI | Waitlist / Enterprise | Figma designs | Design teams |
| Locofy | Free / $25-99/mo | React, Vue, HTML | Figma-to-code |
| PromptUI | $9-29 one-time / $49/mo | React, HTML, Tailwind | Multi-format output |
| Claude/ChatGPT | $20/mo | Any (text-based) | Custom workflows |
Tool-by-Tool Breakdown
v0 by Vercel
The current market leader. v0 generates React components with Tailwind CSS and integrates directly with Vercel's deployment pipeline. If you're already in the Next.js ecosystem, it's the obvious choice.
Pros
- Excellent React output quality
- Iterative refinement works well
- Direct Vercel deployment
- Strong community and examples
Cons
- React/Next.js only
- Limited free tier
- Vendor lock-in concerns
- No plain HTML export
Galileo AI
Generates Figma designs from prompts. Promising concept, but availability is limited (waitlist/enterprise only) and output still requires significant designer refinement.
Pros
- Native Figma integration
- Design-first approach
- Rapid ideation
Cons
- Hard to access
- Outputs need cleanup
- No code generation
- Enterprise pricing unclear
Locofy
Different approach: converts Figma/XD designs to code rather than generating from text. Excellent for design-to-development workflows, but requires existing designs.
Pros
- Multiple framework support
- Respects existing designs
- Good responsiveness handling
- Plugin-based workflow
Cons
- Requires design first
- Not truly text-to-UI
- Complex component logic limited
- Learning curve
PromptUI
Our entry in the space. Focused on practical output: clean React, vanilla HTML, or Tailwind templates. Designed for developers who need production code, not just demos.
Pros
- Multiple output formats
- Clean, readable code
- Flexible pricing (one-time or subscription)
- Credit-based for Starter/Pro tiers
Cons
- Smaller community
- Fewer integrations
- New to market
General LLMs (ChatGPT/Claude)
Not specialized, but surprisingly capable. For simple components or when you need explanation alongside code, general-purpose AI can work. Quality varies significantly.
Pros
- Flexible output format
- Can explain decisions
- Already paying for it
- Iterative conversation
Cons
- Inconsistent quality
- No visual preview
- Requires more prompting skill
- No component library awareness
Real-World Output Comparison
We tested each tool with the same prompt: "Create a pricing page with three tiers: Basic, Pro, and Enterprise. Include feature lists, prices, and call-to-action buttons. Modern, professional styling."
Results Summary
- v0: Best visual output, but React-only. Took 2 iterations to get right.
- PromptUI: Clean output in multiple formats. HTML version worked immediately.
- ChatGPT: Functional but dated styling. Required manual CSS fixes.
- Locofy: N/A (requires existing design)
- Galileo: N/A (waitlist)
How to Choose
Choose v0 if:
- You're building with Next.js/React
- You deploy on Vercel
- Visual quality is the top priority
Choose Locofy if:
- You have designers creating Figma files
- You need pixel-perfect implementation
- The design-to-code workflow matters
Choose PromptUI if:
- You need multiple output formats
- Clean, production-ready code matters
- You want simple credit-based pricing
Use General LLMs if:
- You need simple, one-off components
- You want to understand the code deeply
- You're already paying for ChatGPT/Claude
The Future of Text-to-UI
This space is moving fast. Expect:
- Better component library integration: Tools that know your design system
- Full application generation: Not just components, but complete flows
- Tighter IDE integration: Generate code without leaving your editor
- Improved iteration: More precise refinement instructions
The tools we have today are impressive but imperfect. They accelerate workflows; they don't replace developers. Use them for what they're good at—rapid ideation and boilerplate reduction—and maintain realistic expectations.