GeomCAD: A Benchmark for Precision Reconstruction of Generative CAD Operations from Point Clouds

Point cloud to CAD models are judged by whether their programs execute and resemble the target shape, yet a CAD program is only useful if its parameters are right. We show that these criteria diverge sharply: models whose programs execute on over 90% of inputs recover the exact parameter set for at most 2.7% of them. To measure this gap, we introduce GeomCAD, a benchmark of 4 million executable CadQuery programs, four times larger than any prior program-paired corpus and balanced across extrude, revolve, sweep, and loft, with every parameter an integer on a 1,000-level grid so that exact parameter match is well defined; 36% of its faces are neither planar nor cylindrical, versus at most 12% in prior program-paired corpora. Its protocol GeomCAD-Eval scores exact parameter recovery alongside shape and validity. Our reference model CAD-Exact, trained on GeomCAD, outperforms all zero-shot and fine-tuned baselines on every operation, recovering 27–49% of ground-truth parameter values (best baseline: 13–40%) and matching the target volume within 5% on 49–95% of inputs (best baseline: 36–84%). The corpus, evaluation code, and all checkpoints are released.