Short answer / recommendation
If your priority is tight, repeatable brand consistency at scale (exact colors, fixed compositions, multi-aspect crops, asset library and retraining), lean toward Leonardo AI. If you need high-art, stylized hero creatives quickly and you have a human curator doing final selection/retouch, Midjourney is faster and often produces more striking single images. Both can work — choose by whether you need model control and inpainting/outpainting or pure “look” and speed.

Decision criteria (use these to pick)
- Need to train a private model or fine-tune on brand assets: Leonardo wins.
- Want the most polished, artistic single-image output with minimal setup: Midjourney often wins.
- Multi-aspect crops and exact color matching at scale: Leonardo’s inpainting/outpaint + versioning and asset management are stronger.
- Budget & team: small teams/single designers can start with Midjourney subscriptions. Larger teams that want automation, APIs and model hosting should invest in Leonardo.

Practical workflow (brand-consistent ad creatives)
1) Define constraints before generation: hex color palette, safe area grid (where logo/text must sit), composition templates (hero-left, hero-right, centered), typography overlays as transparent PNG masks.
2) Create “master prompts” and a prompt template with placeholders: [product], [scene], [color-hex], [composition-tag], [mood]. Keep a prompt version log. Use ChatGPT to iterate and standardize prompt templates.
3) Build a small brand dataset (10–50 approved images) to use as references for style and color. Use these for image-conditioning or fine-tuning (Leonardo supports model training / private models; Midjourney can use reference images and seeds but offers less private model control).
4) Generate a base image at the largest required resolution/aspect or at a neutral large canvas. For multi-aspect output, either crop from a larger canvas or use outpainting/inpainting to extend compositions to other ratios.
5) Use mask/inpainting to lock in brand color areas (backgrounds, product surfaces) and preserve safe areas for logos/text. Batch-inpaint to apply color-correct brand backgrounds.
6) QA and color-check with an eyedropper tool against hex swatches; store final seeds/prompts and approved variants in a creative library.
7) Automate batch runs via API where available and create templates for different aspect ratios.

Practical checklist (what to do on every asset)
- Lock down hex palette and save as reference images.
- Use composition template overlay when generating.
- Save seeds/prompts + generation settings.
- Run color-match pass (inpaint/adjust).
- Export master high-res image, then produce aspect variants (crop + inpaint if needed).
- Human QA for brand tone & regulatory copy.

Best-for / Avoid-if
- Best-for Leonardo: teams needing private models, consistent multi-aspect pipelines, strong inpainting/outpainting and asset versioning.
- Avoid Leonardo if you need fast, highly stylized single images and you lack time to set up a model/workflow.
- Best-for Midjourney: creative-first hero ads, rapid ideation, smaller teams.
- Avoid Midjourney if you must guarantee exact colors/compositions at scale or need private model training.

Final note
Budget, team size and whether you’ll invest time to build a fine-tuned workflow determine the right pick. Start with quick experiments (Midjourney or Leonardo free tiers), then standardize the best outputs into a retrainable dataset. If you want to experiment with Midjourney immediately, try it for rapid creative exploration; switch to Leonardo when you need repeatability at scale.

Compare Midjourney and Leonardo AI