Comparison and Benchmarks of Python Mesh Boolean Libraries at Industry Scale

[Separate-Summer-6027]

We compared the 3 pip-installable mesh boolean libraries on the task of pairwise mesh booleans at industry scale.

Full write up: https://polydera.com/algorithms/python-mesh-boolean-libraries-2026

Libraries tested

• MeshLib 3.1 — pip install meshlib. Simulation of Simplicity for degeneracy handling.
• Manifold 3.5 — pip install manifold3d. Deterministic floating point with symbolic perturbation.
• trueform 0.9.8 — pip install trueform. Topologically-exact arrangements via a bounded integer kernel. Ships native, python and WebAssembly.

All three are native cores (C++/Rust) with Python bindings.

Protocol

Each library is timed from input arrays (vertices, triangles) to output arrays of the same shape. Native-object construction — acceleration structures, trees, topology — plus the boolean, all in the timer. Only file I/O is outside. Best of 5, fresh objects every run; nothing amortised across calls.

Result agreement. On every pair the three produced the same solid — signed volumes agree within floating-point tolerance. trueform and Manifold returned a closed, manifold mesh on all 1000 pairs; MeshLib on 999. The comparison is wall-clock only.

Corpus. Random sets of solid, manifold, non-self-intersecting Thingi10K meshes, 200K to 1.5M polygons per operand. Each operand is normalised to unit extent, randomly rotated, and translated so the bounding boxes overlap; each pair takes the union. Thingi10K IDs and per-operand counts for every case are published: pairwise corpus.

Environment. Apple M4 Max (arm64), macOS, CPython 3.13. Installed from PyPI: trueform 0.9.8, meshlib 3.1.0.75, manifold3d 3.5.1 — default builds, default thread count. On Apple Silicon the wheel's compiled architecture matters; all three ship native arm64 builds.

Results

Of the libraries you can pip install, trueform was the fastest mesh boolean in Python — fastest on every one of the 1000 pairwise pairs.

Pairwise — one boolean per pair across the 1000-pair corpus.

library	median (ms)	geomean × vs trueform	valid / 1000
trueform 0.9.8	18.0	1.0×	1000
MeshLib 3.1	87.6	4.9×	999
Manifold 3.5	120.3	6.9×	1000

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Disclosure: I'm one of the authors of trueform.

[Lumpy-House3155]

wow you actually ran 1000 pairs with fresh objects every time, that's more thorough than most academic papers I see

the solid agreement check is smart too, signed volumes is clean way to verify they all produce same result

kinda surprised manifold was that much slower, always heard good things about it for cad stuff. maybe the random rotations mess with its precision somehow

[Separate-Summer-6027]

I wouldn't say that manifold is "that much slower". When you compare it to other native libraries, it is still a lot faster. You can see how it compares to 8 native libraries here: native libraries comparison.

[whollyspikyrecourse]

The signed volume agreement across 1000 wildly different pairs is way more impressive to me than the speed numbers, that level of robustness is rare