AI tool comparison
Layered vs TRELLIS.2 for Mac
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Creative
Layered
Selfies build your closet — AI recommends outfits from what you already own
50%
Panel ship
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Community
Free
Entry
Layered is an iOS app that builds a digital wardrobe from your selfies rather than requiring you to photograph every item individually. Point your camera at yourself, and the AI reads your outfit to catalog what you own — a radically lower-friction approach to wardrobe digitization that most closet apps get wrong by making it too much work to set up. Once your wardrobe is catalogued, Layered becomes a daily outfit advisor: it recommends combinations from what you already own, generates Pinterest-style lookbooks for new pieces you're considering, and creates travel packing capsules calibrated to destination, weather, and luggage constraints. Cost-per-wear tracking surfaces clothes you're ignoring, making decluttering data-driven rather than intuition-based. Built by indie iOS developer Vadim Drobinin, Layered launched on Product Hunt and immediately hit the top five. It's a freemium app — free to start with paid unlocks — and represents the kind of thoughtful, focused indie product that succeeds by solving one problem better than anyone else rather than trying to be everything.
Creative Tools
TRELLIS.2 for Mac
Microsoft's image-to-3D model finally runs on your M-chip Mac
75%
Panel ship
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Community
Paid
Entry
TRELLIS.2 for Mac is a community port that brings Microsoft's powerful image-to-3D generation model to Apple Silicon, replacing every CUDA dependency with Metal-accelerated alternatives. Feed it a single photograph and it outputs a 400K+ vertex mesh with baked PBR (physically-based rendering) textures for metallic, roughness, and base-color properties — as a GLB file ready for Blender, game engines, or AR apps. On an M4 Pro with 24GB RAM, the process takes about 5 minutes. The port is technically substantial: sparse 3D convolution uses Metal acceleration (with PyTorch fallback), mesh extraction is reimplemented in Python, attention uses PyTorch's SDPA, and texture baking leverages Metal rasterization. Every hardcoded CUDA call throughout the original codebase was patched to use the active device dynamically. The result is a model that was previously Mac-inaccessible now running natively without any cloud dependency. For 3D artists, game developers, and AR/VR creators on Apple Silicon — which is most of them these days — this removes a significant barrier. The upstream TRELLIS.2 model is MIT licensed; RMBG-2.0 background removal requires a BRIA commercial license for business use. With 202 HN points, this hit a nerve with creators frustrated that Mac hardware keeps getting excluded from serious ML workflows.
Reviewer scorecard
“The core insight — read outfits from selfies instead of making users photograph items — is a genuine UX breakthrough for this category. Every other closet app dies in onboarding. Layered solves that. Solid indie execution from a developer who clearly uses the product.”
“This is the kind of community port that changes workflows. TRELLIS.2 was genuinely out of reach for Mac users; this brings it home. 5 minutes per mesh on an M4 Pro is totally usable for prototyping and concept work. The Metal acceleration implementation is clean — not a hack.”
“Selfie-based wardrobe reading sounds elegant but breaks down on layering, partial outfits, and anything not visible in a selfie (jeans, shoes, bags). The AI accuracy for attribute tagging in real-world lighting conditions is almost certainly worse than the demo. Fashion AI has been over-promised for a decade.”
“Five minutes per mesh is 10x slower than CUDA on a decent GPU, and the output quality is only as good as the input photo and the model's training distribution. RMBG-2.0 has commercial licensing restrictions that many won't notice until they're already dependent on it. Useful for hobbyists; proceed cautiously for production.”
“Sustainable fashion is a $15B opportunity and AI-powered wardrobe optimization is finally good enough to make a dent in overconsumption. Apps like Layered that show you what you already own and compute cost-per-wear are quietly more consequential than they appear.”
“Every object in the physical world is a potential 3D asset — just photograph it. As ports like this land on consumer hardware, we're approaching a world where any creator can populate 3D environments from their phone camera. The 3D content bottleneck is dissolving faster than people realize.”
“As someone who genuinely wrestles with 'I have nothing to wear' syndrome, this is the app I've wanted for years. The travel capsule generator alone is worth installing — packing for a week trip without overpacking is a real skill gap that AI can fill.”
“Photo to game-ready 3D mesh with PBR textures, no cloud, no subscription, runs on my MacBook. I've been waiting for this workflow for years. Even at 5 minutes a model, this transforms how I source assets for 3D scenes and AR projects. Absolute ship for creative work.”
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