Sloyd
Prompt-based generator for editable 3D assets
What is Sloyd?
Sloyd helps game teams and 3D artists produce usable props quickly, pairing generative input with practical control over shape, detail, and complexity.
Where Sloyd works best
Sloyd is most convincing when you need production-minded props quickly: furniture, weapons, buildings, vehicles, and similar hard-surface objects. Its procedural approach tends to produce cleaner, more coherent geometry than many one-shot text-to-3D systems. Topology, UVs, and polygon budgets are generally suitable for prototypes and background assets, although a finished hero model may still need work in Blender or another DCC. Unusual concepts can drift toward familiar shapes because the generator works within supported asset families.
Workflow, access, and limits
The browser workspace is approachable. Results appear quickly, and variations can be created without learning traditional modeling from scratch. Sloyd uses a credit-based freemium model, with paid subscriptions providing more generation capacity. Separate developer options extend generation into games and other 3D applications.
- Best use: Rapidly filling scenes with consistent manufactured objects and architecture.
- Exports: Textured models can move into common engines and 3D editors.
- Main limitation: Organic creatures and realistic human characters are not its strongest output.
Highlights & limitations
- Parametric controls make generated models easier to art-direct than fixed AI meshes.
- Hard-surface props are produced quickly and often need little cleanup for prototypes.
- Polygon controls help prepare assets for mobile, web, or higher-detail scenes.
- The browser workspace requires no desktop modeling software to start creating.
- API and SDK options can bring asset generation into games and 3D applications.
- The procedural asset library limits how faithfully unusual or highly specific prompts are interpreted.
- Organic creatures and human characters trail its buildings, props, and manufactured objects.
- Credit-based usage makes the cost of repeated experimentation harder to predict.
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