compare-models

Side-by-side comparison of image generation outputs across different AI providers. Use after rendering the same prompt through multiple providers to evaluate quality, style accuracy, and cost.

SKILL.md

GitHub

Compare AI Model Outputs

Analyze and compare interior design renders from different AI providers to help the user choose the best output or provider for their needs.

Pre-flight Checks (MANDATORY — run before comparison)

Before comparing, check what renders and data are available.

!ls projects/${PROJECT_NAME}/renders/*.png 2>/dev/null | head -20 && echo "HAS_RENDERS=true" || echo "HAS_RENDERS=false"
!ls projects/${PROJECT_NAME}/renders/ 2>/dev/null | grep -c '.png' && echo "RENDER_COUNT above"
!ls projects/${PROJECT_NAME}/references/preprocessed/depth_map.png 2>/dev/null && echo "HAS_DEPTH=true" || echo "HAS_DEPTH=false"
!ls projects/${PROJECT_NAME}/references/*.{jpg,jpeg,png,webp} 2>/dev/null && echo "HAS_REFERENCE=true" || echo "HAS_REFERENCE=false"
!ls projects/${PROJECT_NAME}/style-config.yaml 2>/dev/null && echo "HAS_STYLE_CONFIG=true" || echo "HAS_STYLE_CONFIG=false"
!ls projects/${PROJECT_NAME}/notes.md 2>/dev/null && echo "HAS_NOTES=true" || echo "HAS_NOTES=false"

Decision Logic

HAS_RENDERS=false OR RENDER_COUNT < 2?
└── STOP. Need at least 2 renders to compare. Run /render with multiple providers first.

HAS_DEPTH=true AND HAS_REFERENCE=true?
└── Include "Layout Preservation" criterion in comparison.
    Auto-run /validate-layout for each render and include SSIM scores in the table.

HAS_DEPTH=false AND HAS_REFERENCE=true?
└── Layout comparison available but depth map missing.
    Suggest running /preprocess-room first for quantitative layout scoring.
    OR skip layout criterion if user doesn't care about layout fidelity.

HAS_STYLE_CONFIG=true?
└── Read style-config.yaml — use configured colors, materials, style as ground truth for "Style Accuracy" scoring.
    Don't judge style accuracy by memory — check against the config.

HAS_NOTES=true?
└── Read notes.md — check for previous comparison results and feedback trends.
    Append new comparison results to notes.md.

No reference photo (text-to-image only)?
└── Skip "Layout Preservation" criterion entirely — not applicable.

Data-driven comparison > subjective comparison. Use project config as ground truth wherever possible.

Input

  • Multiple rendered images from /render (or image paths provided by user)
  • The original prompt used
  • The target design style

Comparison Criteria

Evaluate each provider's output on:

1. Style Accuracy

  • Does it match the requested interior design style?
  • Are style-specific materials, colors, and furniture correct?
  • Rate: Excellent / Good / Partial / Poor

2. Photorealism

  • Does it look like a real photograph?
  • Texture quality and material rendering
  • Lighting naturalness
  • Rate: Photorealistic / Near-photo / Illustrated / Artificial

3. Composition

  • Camera angle and framing
  • Spatial depth and perspective accuracy
  • Room proportions and scale of furniture
  • Rate: Professional / Adequate / Awkward

4. Detail Quality

  • Fine details: fabric patterns, wood grain, reflections
  • Consistency: no floating objects, impossible geometry, weird artifacts
  • Text/watermark issues
  • Rate: High detail / Medium / Low / Artifacts present

5. Color Fidelity

  • Does the color palette match the design brief?
  • Color harmony and balance
  • Lighting effect on colors (warm/cool cast)

6. Practical Value

  • Could this image be used in a client presentation?
  • Would it work as a design reference?
  • Does it communicate the design intent clearly?

7. Layout Preservation (when comparing against reference photo)

  • Does the generated image maintain the original room's spatial layout?
  • Depth SSIM score (from /validate-layout): quantitative layout fidelity metric
  • Wall positions, window placements, furniture depth ordering preserved?
  • Rate: Identical / Good / Fair / Distorted

Output Format

## Model Comparison: [Style] [Room]

| Criteria         | Gemini | OpenAI | Stability | Grok |
|-----------------|--------|--------|-----------|------|
| Style Accuracy  |   ★★★★ |  ★★★★  |   ★★★★    | ★★★  |
| Photorealism    |   ...  |  ...   |   ...     | ...  |
| Composition     |   ...  |  ...   |   ...     | ...  |
| Detail Quality  |   ...  |  ...   |   ...     | ...  |
| Color Fidelity  |   ...  |  ...   |   ...     | ...  |
| Layout Fidelity |   ...  |  ...   |   ...     | ...  |

### Best For:
- **Client presentation**: [provider] — [reason]
- **Design exploration**: [provider] — [reason]
- **Quick iteration**: [provider] — [reason]
- **Budget-conscious**: [provider] — [reason]

### Recommendations:
- [Specific refinement suggestions per provider]

Suggest /refine for the most promising output to iterate further.

Session Relevant Skills

  • /refine — after identifying the best provider output, use /refine to iterate on that specific prompt+provider combination. Pass the original prompt and specific feedback from the comparison.
  • /render — if the comparison reveals all outputs are poor, consider re-rendering with adjusted prompts. Go back to /generate-prompt if the prompts themselves need rework.
  • /generate-prompt — if comparison shows systematic prompt issues (wrong style keywords, bad composition across all providers), the prompts need regeneration, not refinement.
  • /style-guide — reference when evaluating style accuracy. Use the style's specific keywords/materials/colors as the ground truth for scoring.
  • /edit-design — if one render is close but needs specific changes (swap a piece of furniture, adjust lighting), /edit-design can target those changes rather than re-rendering from scratch.
  • /validate-layout — provides quantitative SSIM scores for layout comparison. Run on each provider's output to get objective layout fidelity metrics.
  • /preprocess-room — the source of truth for the original room's depth map used in layout comparison.

Gotchas

  • Compare apples to apples: Ensure all images used the same (or equivalent) prompt. Different prompts produce different styles — that's a prompt issue, not a provider issue.
  • Don't compare more than 4-5 providers at once: The comparison table becomes unwieldy. Focus on 2-3 most promising providers.
  • Provider strengths are style-dependent: Stability excels at textured/rustic styles, DALL-E at clean modern, Midjourney at atmospheric/dramatic. A provider ranking for Scandinavian may be reversed for Baroque.
  • Practical value matters most: A slightly less photorealistic image that clearly communicates the design intent is more useful than a photorealistic image with wrong style elements.
  • Layout comparison only applies when there's a reference photo: For text-only generations (no reference room), skip the layout criterion entirely.
  • Different providers have different layout control capabilities: Stability AI structure control and Gemini image editing can preserve layout; DALL-E and Midjourney cannot. Factor this into comparisons.