Migrate from leonardo-ai to playground.
1 documentation-derived translation pattern — what carries over and what to watch for. Cited to the Feature Parity Map; the audit tells you whether the move is worth it.
Both tools are multi-model, prompt-driven image generators, so the core workflow transfers directly: rewrite the Playground prompt and pick a comparable Leonardo model. Where you relied on GPT Image 2 in Playground for typography-heavy posters, choose a Leonardo model with strong prompt adherence (e.g. Phoenix, or third-party FLUX/Ideogram available in Leonardo) and use Leonardo's prompt-enhancement option. Re-create any saved designs as fresh generations; there is no design-file import between the two. Move recurring asset jobs onto Leonardo's API once volume justifies it, since Leonardo exposes a production REST API on its higher tiers.
- Warning: Leonardo meters generation with a daily/monthly token system (tokens deducted by compute cost) rather than Playground's per-3-hour image cap plus monthly model credits, so estimate usage in tokens, not image counts.
- Warning: Playground is framed as a design studio with templates and a built-in design editor for finished assets (logos, t-shirts, social graphics); Leonardo is generation-and-canvas-first and does not ship Playground's design-template library, so template-driven workflows must be rebuilt as prompts or done elsewhere.
- Warning: Model line-ups only partly overlap — Playground leans on GPT Image 2 and Nano Banana Pro (and also offers Seedream), while Leonardo centers on its own Phoenix 0.9/1.0 models plus third-party integrations (FLUX, Ideogram, Seedream), so default model choices and identical prompts will not produce identical output.