How to Migrate From Midjourney to Leonardo AI
Midjourney is a strong general-purpose image generator with a distinctive aesthetic. For game developers and environment artists, it can produce concept art and reference material that looks polished. But it has two gaps that eventually send people looking elsewhere: you can't train custom style models on it, and it doesn't generate tileable textures natively.
Leonardo AI was built with creative production workflows in mind. The platform centers around "Elements", trained LoRA-style models that you either train yourself or pull from the community library. For game asset workflows, this means you can train an Element on your game's specific art style and apply it consistently across every asset you generate, from character concept sheets to environment props. The tiling texture feature, which outputs cleanly repeating textures for use in game engines, is a practical tool that has no equivalent in Midjourney. If you're producing 2D or 3D game assets, the migration case is strong.
What's actually different
Midjourney is a closed model accessible only through their platform. You have no access to the underlying weights, can't fine-tune, and style consistency across sessions relies on --sref image references and prompt discipline. The output is beautiful but lives inside Midjourney's aesthetic envelope.
Leonardo AI runs on a combination of Stable Diffusion-based models (including SDXL and their proprietary Phoenix model) with a platform layer that adds fine-tuning, Element management, and a suite of production tools. You interact through the web app or API.
| Dimension | Midjourney v6.1 | Leonardo AI (Phoenix + Elements) |
|---|---|---|
| Custom model training | No | Yes (custom Elements) |
| Style consistency | --sref image references | Trained Elements + same seed |
| Tiling textures | No | Yes, dedicated tiling mode |
| Negative prompts | --no parameter | Standard negative prompt field |
| ControlNet | No | Yes |
| Prompt style | Keyword compressed | Natural language + weights optional |
| API access | None | Yes (Leonardo API) |
| Asset types | Images only | Images, textures, canvas editing |
| Generation credits | Monthly GPU minutes | Token-based credit system |
The Phoenix model is Leonardo's flagship proprietary model and performs closer to Flux/SDXL quality than earlier SD-based models. For game assets specifically, the Phoenix model combined with a trained Element produces very consistent results.
Mapping your existing prompts
Style references. Midjourney's --sref URL is the closest thing to an Element. The equivalent in Leonardo is: create a Custom Element by uploading 10-20 images that define your desired style, train it (takes 20-30 minutes), and then apply it at a specified weight (typically 0.5-0.8) in your generations. This is more work upfront but produces more consistent results than image references, because the Element is baked into the generation rather than referenced at inference time.
Character references. Midjourney's --cref URL for character consistency maps to Leonardo's "Character Reference" feature in the Alchemy+ mode, or more robustly to a Character Element you train specifically on your character design.
Aspect ratio. Midjourney uses --ar 4:3. Leonardo has a dimension selector in the UI. For game assets, common setups: 1024x1024 for square sprites, 512x512 for lower-res items, 1024x576 for widescreen environment art.
Negative prompts. Midjourney uses --no inline. Leonardo has a dedicated negative prompt field. Typical game asset negative: blurry, watermark, text, UI elements, interface, low quality, deformed, inconsistent lighting.
Prompt structure. Midjourney rewards dense descriptors: medieval shield, ornate, silver, celtic knotwork, fantasy RPG, hero inventory item. Leonardo's Phoenix model handles this similarly, but you can also use Stable Diffusion-style attention weights if you're on an SDXL-based model: (celtic knotwork:1.3), (silver metallic:1.2). With Phoenix, plain natural language tends to work better than weighted syntax.
Tiling textures. This has no Midjourney equivalent. In Leonardo, enable the "Tiling" option in the advanced settings. Prompts for textures work best when you describe the surface material explicitly: tileable stone cobblestone texture, worn medieval, top-down view, diffuse map, no shadows, uniform lighting. The tiling toggle makes the output tile on all four edges.
The actual migration steps
1. Create a Leonardo account. Go to leonardo.ai and sign up. The free tier gives 150 tokens per day. Each standard generation costs around 4-8 tokens depending on resolution and model. For active production use, the Apprentice plan at $12/month gives 8,500 tokens monthly.
2. Explore the model library first. Before training custom Elements, check the existing community Element library. Search for terms like "pixel art," "isometric game asset," or the art style closest to your project. You may find an existing Element that saves you the training step.
3. Run baseline comparisons. Import your top 20 Midjourney prompts and run them through Phoenix without any Elements. This gives you a baseline sense of what the model does by default, and which prompts need adjustment.
4. Train your first Element. For a game project, gather 15-20 images that represent the target art style. These can be your existing concept art, reference images, or strong Midjourney outputs you already have. Upload them to Leonardo's Element training interface, name your Element, and start the training job. The training takes 20-40 minutes.
5. Apply the Element in generations. When creating images, click the Elements section, add your trained Element at a weight between 0.5 and 0.8. Lower weights let the prompt drive more of the output; higher weights push harder toward your trained style. Experiment with this for each asset type.
6. Set up tileable texture workflow. Create a dedicated workspace for textures. Enable Tiling in Advanced settings. Build a prompt template for each material type in your game (stone, wood, metal, fabric, dirt) and save them. Running a batch of 20 textures from a template takes a few minutes and produces a library of tileable assets directly usable in Unreal Engine or Unity with standard PBR material workflows.
7. Connect the API if needed. Leonardo's REST API accepts the same parameters as the UI. For CI/CD pipelines that generate asset variants automatically, or for tools that integrate asset generation into a game editor plugin, the API is practical.
Gotchas you'll hit
Element overfitting. If your training dataset is too similar (all the same art style, no variety in composition), the Element can overfit and produce images that all look like clones of the training images regardless of the prompt. Use a varied training set with different compositions and angles.
Credit burn. Leonardo's token system burns faster than expected if you're generating at high resolution or using Alchemy (the enhanced quality mode). Alchemy outputs look better but cost more tokens per image. Budget for this before switching a heavy workflow.
Phoenix vs. SDXL model selection. Leonardo offers multiple base models. Phoenix is the most capable but not always the right choice, for pixel art, older SD 1.5-based fine-tunes often produce more authentic results. Test across models for your specific asset type before committing to one.
No Discord community style pipeline. Midjourney's Discord community and /explore feature gives you access to thousands of prompts and styles instantly. Leonardo has a community feed but it's less developed. You'll spend more time developing prompt templates from scratch.
Tiling doesn't mean PBR-ready. Leonardo's tiling output is a diffuse/albedo map. For physically-based rendering in modern game engines, you'll still need to generate or derive the normal map, roughness map, and metallic map separately. Tools like Materialize or the Substance suite handle this from a tiling base image.
When NOT to switch
If your primary output is concept art, matte paintings, or editorial illustrations where Midjourney's aesthetic is an asset, the switch to Leonardo doesn't improve much. Midjourney's trained aesthetic sense and community style library are advantages for artistic work.
For projects that don't require consistent style across many assets, the overhead of training Elements isn't justified. Midjourney's image reference system is faster when you're generating a handful of images for a mood board rather than a production library.
If you rely on Midjourney's community features, studying others' prompts, following artists, the social discovery aspect, Leonardo's community tooling is thinner.
Switch to Leonardo when you need: consistent game art style across 100+ assets, tileable PBR-ready textures, an API you can wire into a production pipeline, or the ability to train and reuse a custom style model. For those production use cases, Leonardo's platform features are purpose-built in ways Midjourney's general-audience tool is not.