Pixal3D vs MeshCrunch

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Pixal3D compared with MeshCrunch
Detail	Pixal3D	MeshCrunch
What it does	Image to textured 3D model from a photo	Simplify 3D meshes, generate LOD chains, and export turntable clips
Stage	Not given	Not given
Founded	Not given	Not given
Based in	Not given	Not given
Pricing model	Freemium	Freemium
Pricing	Not given	Free: $0 with account or no account required (10 processing credits per 24 hours, up to 50 MB per file, 250 MB storage). Starter: $15 per month (500 processing credits per month, up to 250 MB per file, 5 GB storage, 7-day free trial). Pro: $35 per month (2500 processing credits per month, up to 1 GB
Key features	Image-to-3D generation with pixel-aligned reconstruction Textured GLB export with PBR materials Trellis 2 comparison lane for alternative reconstructions Free browser-based GLB inspection and conversion tools Text-to-motion generation with Hunyuan Motion Adjustable output settings for quality and file size	Mesh Simplification: reduce triangle count with quadric-error decimation while preserving silhouette LOD Chains: generate multiple detail levels from one high-poly asset Watertight Rebuild: close holes and rebuild surfaces on damaged models Mesh Inspection: detect non-manifold edges, holes, winding, missing UVs and platform compatibility 3D File Converter: convert between OBJ, STL, PLY, OFF and GLB formats 3D Model Viewer: inspect models with orbit controls, grid and wireframe 3D GIF Maker: export rotating GIF or MP4 turntable animations from models REST API: programmatic access for scripts and asset pipelines MCP server: AI client integration for agents like Claude
What makes it different	Pixel-aligned fidelity preserves source image detail and silhouette in 3D geometry Pay-per-job pricing instead of monthly subscriptions Free browser tools run locally without consuming credits Inspect and review results before spending credits Compare Pixal3D and Trellis 2 lanes on the same source image	Queue-backed pipeline with Postgres state tracking maintains work across device refreshes and crashes Data privacy: models never used for ML training, stored in private object storage with signed expiring downloads Owned hardware infrastructure with zero-egress storage keeps economics viable for large 3D files Same account and allowances across Studio, REST API and MCP interfaces Processing split by tier: paid work runs on dedicated workers not held up behind free traffic
Community votes	0	0
DR (Domain Rating by Ahrefs)	22 no change since last check	4 no change since last check
Trust Flow (Majestic)	6	7
Citation Flow (Majestic)	14	21
Referring domains (Majestic)	69	12

4 details filled in for both companies.

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