Figma Make vs Galileo
Detailed side-by-side comparison to help you choose the right tool
Figma Make
AI Development Assistants
Figma's native generative AI design tool that turns natural-language prompts into editable UI designs, prototypes, and layouts directly inside the Figma canvas — no external plugins or exports required.
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CustomGalileo
🔴DeveloperAI Evaluation
Galileo review 2026: enterprise AI evals, observability, guardrails, and Luna evaluator models for RAG and agents — features, pricing, pros, cons.
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CustomFeature Comparison
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💡 Our Take
Choose Figma Make if your team already works in Figma and needs generated designs to slot directly into existing files with full design-system support, Dev Mode handoff, and Supabase-powered backends. Choose Galileo AI if you want a dedicated, standalone AI design generator with potentially more creative output variety and you don't mind exporting and importing assets into your design tool afterward.
Figma Make - Pros & Cons
Pros
- ✓Native Figma integration produces fully editable vector layers, auto-layout frames, and real component instances — not flattened images requiring reconstruction
- ✓Automatically applies your team's existing design system tokens, variables, and published component libraries to generated outputs, dramatically reducing on-brand cleanup time
- ✓Supabase integration (added in 2025) lets users ship functional web apps with authentication, data storage, and private APIs directly from a prompt — no coding required
- ✓Iterative conversational refinement converges on a desired layout in 2–3 prompts rather than full regeneration cycles required by most competitors
- ✓Seamless handoff to developers via Figma's Dev Mode, preserving accurate CSS specs, spacing values, and exportable assets for engineering teams
- ✓Available across all Figma plan tiers — from free Starter to $75/editor/month Enterprise — making it accessible to Figma's 4M+ existing users without a separate subscription
Cons
- ✗Generation quality depends heavily on prompt specificity; vague prompts produce generic or off-brand layouts that require manual rework
- ✗AI generation quotas on lower-tier plans (Starter and Professional at $12–$15/editor/month) can feel restrictive for teams running heavy ideation sprints
- ✗Outputs are locked into the Figma ecosystem — there is no native export to Sketch, Adobe XD, or Penpot without third-party conversion tools
- ✗Highly custom or illustrative styles (3D elements, complex illustrations, non-standard layouts) are not well-supported; Make is optimized for standard UI patterns
- ✗Design system adherence can degrade with poorly structured or undocumented component libraries, requiring manual component swaps after generation
Galileo - Pros & Cons
Pros
- ✓Luna evaluators are dramatically cheaper than LLM-as-judge — eval coverage can stay on in production
- ✓End-to-end coverage: evals + traces + guardrails + agent root-cause from one vendor
- ✓Strong enterprise compliance posture (VPC, audit, SSO) suitable for regulated industries
Cons
- ✗No public pricing — every conversation starts with sales, which slows POC adoption
- ✗Heavier and more opinionated than open-source [/tools/langfuse](/tools/langfuse) or [/tools/arize-phoenix](/tools/arize-phoenix) — early-stage teams may find it overkill
- ✗Luna evaluators are proprietary — verify quality on your domain before assuming they replace LLM-judge in your stack
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