Overview
How might we design output comparison view so people can trust and act on AI output?
When this pattern fits
- Ideal for content generation tools, code generation platforms, and creative workflows where comparing multiple outputs improves decision-making.
When to skip or lighten it
- Single deterministic outputs.
- Mobile screens too narrow for meaningful side-by-side (stack with a toggle instead).
- Comparisons across incompatible modalities without alignment.
States
State model coming soon
Key UX elements
Key UX elements coming soon
Anti-patterns to avoid
Comparing runs that used different hidden prompts without saying so.
No way to pick a winner and discard the rest.
Side-by-side without synced scroll for long code.
Keeping infinite variants until the UI stalls.
How products use it
| Product | Implementation |
|---|---|
| Midjourney | Grid and variant comparisons for images. |
| ChatGPT | Compare alternate answers or canvas versions. |
| GitHub Copilot | Alternative suggestion comparison in editors. |
| Design tools | Variant frames for AI-generated UI options. |
Implementation
Copy this prompt to generate a production-ready implementation in Cursor, Claude Code, Lovable, or any AI coding agent.
Generate a production-ready implementation of the "Output Comparison View" AI interface design pattern.
Pattern Definition:Frequently asked questions
When is comparison better than a carousel?
When users need simultaneous judgment. Carousels save space; comparison improves evaluation quality.
What metadata should each pane show?
Model or preset, timestamp, and any differing parameters. Hide nothing that affected the result.
How does this relate to regeneration carousel?
A carousel stores variants sequentially. Comparison view displays them concurrently for judgment.
How many panes?
Two is default; four for image grids. Beyond that, use a gallery with a shortlist.