Gemini 3 vs. Claude Opus 4.5 vs. GPT-5.1 Codex: Which AI model is the best designer?

The host introduces a controlled experiment to test which AI model is the best designer by having Gemini 3, Opus 4.5, and GPT-5.1 Codex redesign the same blog page using an identical prompt. The test focuses on visual design, user experience improvements, and SEO optimization capabilities.

• •Used exact same prompt across all three models: redesign for visual appeal, UX, and SEO best practices
• •Testing models on an existing, poorly-designed blog page rather than creating from scratch
• •All tests conducted in Cursor IDE with identical input code and directory structure
• •Goal is to identify which model fits which role in a development workflow

Gemini 3 Pro executed quickly with chain-of-thought reasoning but produced a serviceable rather than exceptional design. It created a hero image layout with card-based blog posts, hover effects, and basic improvements, but lacked full visual context and had spacing issues with navigation elements.

• •Generated hero image of most recent post plus three-column card layout with hover zoom effects
• •Added tagging and release dates but didn't handle pagination or missing images well
• •Navigation spacing issues - tags too tight with rest of navigation
• •Fast execution but lacked the planning step that other models demonstrated
• •Did not meet its reputation as 'best designer' in this test

Claude Opus 4.5 demonstrated the most sophisticated approach by creating a detailed to-do list before implementation, resulting in the highest quality design. It pulled existing design assets, added thoughtful UI touches like hover arrows and reading time estimates, and handled edge cases like missing images with placeholder graphics.

• •Triggered tool call to create step-by-step to-do list: redesign listing page, improve layout, enhance post display, add SEO structure
• •Planning capabilities led to 20-30% better design quality than Gemini 3
• •Pulled existing brand assets (background images, design rings) from repository
• •Added polished details: hover arrows on CTAs, reading time estimates, author info, smart placeholder images for missing content
• •Created improved newsletter CTA component at bottom of blog posts
• •Most production-ready output requiring minimal additional work

GPT-5.1 Codex performed poorly on design despite being OpenAI's leading coding model. It produced generic 'AI purple gradient' styling, selected inappropriate logo assets, created non-functional navigation elements, and failed to display existing blog posts correctly. The model excels at back-end work but should not be used for front-end design.

• •Generated generic purple-to-blue gradient ('AI slop purple') instead of brand-appropriate design
• •Selected wrong logo variant that didn't work on colored backgrounds
• •Created non-functional UI elements: featured image with no context, broken category links, missing blog posts in library view
• •Less detailed planning compared to Opus 4.5 (investigate, redesign, apply SEO vs. specific component-level tasks)
• •Best copywriting among the three models but worst visual and functional design
• •Conclusion: GPT-5.1 Codex belongs in back-end development, not front-end design

Analysis of the technical SEO and functional changes each model implemented beyond visual design. Gemini 3 added JSON-LD schema and related articles, Opus 4.5 focused on metadata and user experience enhancements, while GPT-5.1 Codex made minimal SEO improvements despite the prompt requesting them.

• •Gemini 3: Added JSON-LD schema, breadcrumbs, semantic HTML, related articles functionality, and metadata to individual blog posts
• •Opus 4.5: Implemented reading time badges, category pills, breadcrumbs, graceful empty states, but didn't explicitly call out JSON-LD
• •GPT-5.1 Codex: Basic metadata and schema.org implementation, shortest and least detailed summary of changes
• •All models went beyond just the blog homepage to modify individual post layouts
• •Gemini 3 and Opus 4.5 both added related articles and improved post metadata

Key insight on model switching strategy: different AI models excel at different parts of the development workflow. Rather than using one model for everything, assign models to specific roles based on their strengths - design, planning, back-end coding, SEO engineering, etc.

• •Model switching is essential - no single model excels at all tasks (writing, design, image gen, planning, back-end coding)
• •Opus 4.5 best for front-end design and detailed planning work
• •GPT-5.1 Codex better suited for back-end engineering despite being a 'coding model'
• •Testing models on repeated use cases helps identify where each fits in your workflow
• •Planning capabilities dramatically impact design quality - models with explicit planning steps produce better results
• •Small component redesigns (widgets, CTAs) can be more impressive than full page designs

Recap of the experiment results and practical workflow advice. In under 20 minutes, three complete alternative designs were generated with different SEO implementations, demonstrating the power of AI-assisted design iteration. The winner, Opus 4.5, produced production-ready code that was immediately shipped.

• •Clear winner: Anthropic's Opus 4.5 for design, usability, and SEO implementation
• •Generated three complete alternative designs in under 20 minutes - impossible speed for human designers
• •Hypothesis: Opus 4.5's superior performance due to better front-end training data and detailed planning capabilities
• •Host shipped the Opus 4.5 design to production immediately after the test
• •Natural language prompts (as you'd speak to a colleague) are sufficient for model comparison
• •This workflow enables rapid iteration and A/B testing of design alternatives