Midjourney vs Leonardo AI for consistent SKU variations

Short answer
For tight, repeatable SKU photos across hundreds of items, you’ll usually get more reliable photorealistic control using a pipeline that favours an image-conditional model with inpainting and API batch tools (Leonardo-style workflows). Midjourney is excellent when you need stylized lifestyle or hero images and have an artist to normalize output in post. Both can work — choice depends on how photorealistic you need results, your budget, and how much post-processing you can do.

Recommendation
If your priority is pixel-perfect consistency (color accuracy, exact angle, identical lighting): use a Leonardo-style image-to-image + inpainting pipeline with a locked camera template and API-driven batching. If you want on-brand stylized assets and can accept some variation or post-editing, use Midjourney and enforce consistency via strict prompt tokens, seeds, and heavy prompt engineering.

Decision criteria (pick the one that matters most)
- Photorealism & tight consistency: Leonardo-style (image conditioning + inpainting) wins.
- Stylized/creative hero shots: Midjourney is stronger.
- Automation & scale: prefer a tool with API/batch export and inpainting (Leonardo or API-enabled setups).
- Budget & team skill: Midjourney is faster to iterate for artists; Leonardo-style + automation costs more but reduces manual QC.
- Post-production tolerance: if you can retouch, Midjourney + a single standard retouch step is viable.

Practical prompt & seed guidance (templates)
- Start with a camera-locked template image (same crop/aspect/angle): use that image as the primary image prompt.
- Product photo base prompt (photorealistic):
" studio lighting, seamless white background, 35mm, f/8, ISO100, front 30° angle, exact color #FF6A00 (or Pantone 158), matte texture, no reflections, realistic fabric detail, shot from 1.2m, do not add hands or props --seed 12345 --ar 4:5"
- Stylized hero prompt (Midjourney):
" lifestyle, warm golden hour light, model holding product, shallow depth of field, cinematic color grade, consistent brand tone, --seed 12345 --stylize 50 --ar 16:9"
- For texture swaps: include texture prompt like "velvet texture, 600 DPI detail, consistent grain" and pass a texture mask for inpainting.

Seed & reproducibility rules
- Lock seed for the composition baseline. Use the same seed across all SKUs for identical camera/lighting/composition.
- Vary only color/texture via image overlays or small prompt token changes (hex or Pantone). Keep seed constant for each group.
- Log model version, seed, aspect ratio, and full prompt text in a CSV tied to SKU IDs.

Checklist before mass generation
1) Create one master template photo (camera, lighting, angle). 2) Create or capture clean masks for product area. 3) Test 5 SKUs: run identical seed + texture/color inputs. 4) Verify color accuracy with color target or Pantone swatch. 5) Run batch via API/automation. 6) QC 3% random sample and full-proof file naming/versioning.

Best-for / Avoid-if
- Best-for: brands needing consistent, photorealistic product shots with minimal manual retouching (Leonardo-style). Also good for quick texture swaps using inpainting.
- Avoid-if: you need bespoke artistic hero images where variation is acceptable — use Midjourney.

When this depends
- Budget: automation + image-conditioning costs more.
- Skill level: Midjourney is friendlier for prompt-only workflows; image-inpainting pipelines require more ops/dev.
- Team size/output quality: larger teams benefit from API-driven, repeatable pipelines.

If you want, I can draft exact Midjourney and Leonardo-style prompt files and a 10-SKU test plan (incl. masking and naming conventions).

Compare Midjourney and Leonardo AI