Midjourney vs Leonardo AI for product mockups

Short recommendation
For 100+ photorealistic catalog mockups where consistent angle and lighting are critical, favor Leonardo AI for a production pipeline focused on repeatability, templating, and inpainting. Use Midjourney only if you already depend on its aesthetic style or want a more “luxury/stylized” look and are prepared for more manual retouching to reach deterministic results.

Why (decision criteria)
- Photorealism & material fidelity: Leonardo’s photoreal models and inpainting tools tend to produce catalog-ready materials (glass, metal, fabric) with fewer stylistic artifacts. Midjourney is excellent for high-end visuals but can introduce stylization that’s hard to remove.
- Consistency & control: Leonardo supports templating, image-to-image/inpainting workflows and better project-level controls for repeating the same camera/lighting across batches. Midjourney can be forced toward consistency using seeds and reference images, but it’s more brittle.
- Batching & automation: Leonardo’s project/workflow features and API options are more suited for bulk runs and programmatic variations. Midjourney has APIs and Discord automation but often needs more manual orchestration.
- Cost per usable image: depends on subscription, resolution, and post-processing. Expect ballpark $0.10–$2+ per final approved image (lower if you automate many low-res drafts then upconvert offline). Choose per-image vs. subscription models based on volume.

Prompt/template starter (use as a master template and tweak per product)
[Product name], photographed as a studio catalog shot. Material: [material keywords]. Angle: 3/4 view, camera at 45° to product, 50mm lens, shallow depth of field. Lighting: softbox key from 11 o’clock, fill at 4 o’clock, neutral white balance, subtle rim light. Background: seamless white/gray (or transparent). Output: photorealistic, realistic shadows and reflections, accurate scale, no text, no distortion. Render size: [spec]. Seed: [lock-seed if supported]. --no stylization.

Batching practicals
- Create a single “angle/lighting” reference image to use as the template for every generation (image-to-image/inpaint). Lock camera parameters (focal length, angle) in prompts or model fields.
- Run iterative tests: 10 products × 3 style variations to converge on a prompt that yields consistent results, then scale.
- Use inpainting to swap products onto the same finished background/lighting plate—this drastically increases consistency and reduces postwork.
- Automate via API or scripts: feed product JSON (title, color, texture) into prompt template; save seeds and variant IDs.

Checklist before mass generation
- Choose final model and confirm license/commercial terms.
- Create and approve a reference plate (angle + lighting).
- Build master prompt and lock seeds/camera params.
- Run a 10-product pilot, refine prompts.
- Set up batching script or project, enable high-res upscales only for finalists.
- Export naming convention + metadata for catalog ingestion.

Best-for / Avoid-if
- Best for Leonardo: large catalogs, photorealism, templated inpainting, programmatic pipelines. Avoid if you need highly stylized, one-off art pieces.
- Best for Midjourney: brand-forward, stylized hero shots, creative product imagery. Avoid if you need pixel-perfect consistency across 100+ items.

Dependencies
Your choice depends on budget (subscription vs per-image credits), team skill (prompt + inpainting experience), whether you need API automation, and final quality tolerance. If you’d like, share one sample product and I’ll draft a tuned master prompt and a 10-item pilot plan.

Compare Midjourney and Leonardo AI