AI models ranked for UX/UI design workflows. Scored with bonuses for vision (analyzing screenshots and wireframes), image output (generating mockups and design assets), JSON mode (structured design tokens), large context windows (processing design systems), and streaming (real-time design iteration).
| # | Model | Score |
|---|---|---|
| 1 | Claude Opus 4.7Anthropic | 113 |
| 2 | GPT-5.5OpenAI | 111 |
| 3 | Gemini 3.1 Pro Preview Custom ToolsGoogle | 110 |
| 4 | Gemini 3.1 Pro PreviewGoogle | 110 |
| 5 | GPT-5.4 ProOpenAI | 110 |
| 6 | GPT-5.4OpenAI | 110 |
| 7 | GPT-5.5 ProOpenAI | 109 |
| 8 | GPT-5.2 ProOpenAI | 109 |
| 9 | Claude Opus 4.6 (Fast)Anthropic | 108 |
| 10 | Claude Opus 4.6Anthropic | 108 |
| 11 | GPT-5.2-CodexOpenAI | 108 |
| 12 | GPT-5.2OpenAI | 108 |
| 13 | Grok 4.20xAI | 107 |
| 14 | GPT-5.3-CodexOpenAI | 107 |
| 15 | GPT-5 ProOpenAI | 107 |
| 16 | Gemini 3 Flash PreviewGoogle | 106 |
| 17 | Grok 4xAI | 106 |
| 18 | Grok 4.20 Multi-AgentxAI | 106 |
| 19 | GPT-5.1-Codex-MaxOpenAI | 106 |
| 20 | GPT-5 CodexOpenAI | 106 |
| 21 | GPT-5OpenAI | 106 |
| 22 | GPT-5.3 ChatOpenAI | 105 |
| 23 | GPT-5.1OpenAI | 105 |
| 24 | GPT-5.1-CodexOpenAI | 105 |
| 25 | GPT-5.1-Codex-MiniOpenAI | 105 |
| 26 | o3 Deep ResearchOpenAI | 105 |
| 27 | o3 ProOpenAI | 105 |
| 28 | o3OpenAI | 105 |
| 29 | GPT-5.1 ChatOpenAI | 105 |
| 30 | Claude Sonnet 4.6Anthropic | 103 |
Vision capability enables AI to analyze existing UI screenshots and wireframes to understand patterns and context. Image output allows generating high-fidelity mockups, prototypes, and design variations directly from descriptions, accelerating design iteration.
JSON mode enables extracting and generating structured design tokens (colors, typography, spacing, components). Large context windows (100K+) support processing complete design system documentation, component libraries, and design specifications in a single conversation.
Vision models analyze UI screenshots to evaluate accessibility (contrast, font sizes, color use), usability patterns, and WCAG compliance. Large context enables reviewing full user flows and identifying design inconsistencies across multiple screens.
Streaming capability enables real-time generation of design suggestions, rationale, and code as designers describe changes. Vision + streaming creates interactive design assistant experiences for live feedback on typography, layouts, and component refinements.
Vision models analyze existing interfaces for usability issues, accessibility compliance, and design consistency. They generate user flow diagrams, wireframe descriptions, and component specifications. Models write CSS and design system code from visual references.
Models analyze user interview transcripts, survey responses, and session recordings (via vision) to identify patterns. Reasoning synthesizes findings into personas, journey maps, and design recommendations. They generate discussion guides and survey instruments.
Vision models audit component consistency. Code generation creates component documentation and usage examples. JSON mode outputs structured design tokens. Reasoning ensures accessibility compliance (WCAG AA). Large context processes entire design systems for consistency checks.
Models write button labels, error messages, onboarding flows, empty states, and tooltip text optimized for clarity and user action. They generate A/B variants, localized copy, and accessible descriptions. Reasoning ensures copy aligns with user intent and task flow.