skulitom/Nestbolt

In the frozen v1 benchmark, **8.5% less material at the median than the best of Deepnest, SVGnest and Sparrow**
at equal 60-second budgets, and 9.6% at 300 seconds, in the final benchmark run
(fresh seeds, ten held-out jobs). Sparrow still wins 8 of the 56 jobs at 60 seconds
(details, every number).
Free, open-source nesting for people who cut **fixed sheets**: laser cutters, CNC
routers, plasma, waterjet, fabric and leather. Nestbolt arranges parts so they use
the least material. It runs in your browser
(nothing is uploaded), on the command line, and as an MCP server that AI agents
can call.
Open the browser app ·
Download a release ·
Connect an AI agent
The current development build supports editable LightBurn project nesting, lead-in
allowances and improvements for large curved drawings. The v1.1 plan is still
in progress; current verification and remaining work distinguish
completed features from open checks. Downloaded releases contain the features
listed in their own release notes. The hosted browser was last deployed from
v0.1.0; to try the
newer browser features, build the development app locally.
The benchmark figures below belong to the frozen 75cbb32 build, not a new
comparison of the development build.
451 parts on one 850 × 425 mm sheet in 120 seconds on one CPU core: DejaVu Sans
Bold glyphs in four sizes with their exact Bézier outlines, 90° rotations and
1 mm spacing. 29 letters sit inside the holes of others, and the unused material
stays as one clean offcut along the top. The layout passed the independent
validator. Rebuild it with python scripts/make_showcase.py --nest 120.
How it compares
Final acceptance run (2026-10-13): 75 frozen sheet jobs (35 academic, 40 maker,
ten of them held out from all tuning), equal time budgets, one CPU core per tool,
five fresh seeds each, every layout checked by an independent validator. The
comparison is against the best of Deepnest,
SVGnest and Sparrow
on each job, each with the better of its two settings.
| Budget | Valid Nestbolt layouts | Less material than the best competitor (median) | Wins or ties |
| --- | ---: | ---: | ---: |
| 60 s | 375/375 | **8.5%** | 48 of 56 |
| 300 s (long subset) | 60/60 | **9.6%** | 11 of 11 |
At 60 s Nestbolt uses less material than Deepnest on all 55 jobs where Deepnest
produced a layout (median 9.9%) and than SVGnest on all 36 (14.4%). Sparrow, which
Nestbolt builds on, wins 8 jobs. Seven are one-sheet jobs that Nestbolt hands to
Sparrow itself after its own first layout, so Sparrow runs with slightly less time
there; it is 0.03-2.4% better on them. The eighth (two sheets) is 0.34% better.
That misses the project's own 60-second bar (wins or ties on 90% of jobs and never
more than 1% worse); the 300-second, strip-parity and speed bars are met
(status).
One benchmark job exactly as nested in a 60-second development run (m-mechanical-frame-inserts,
seed 0, sheet turned to landscape): 138 parts, all 39 inserts placed inside frame
windows, everything packed into 56% of a 2440 × 1220 mm sheet so the rest stays one
offcut. The best competitor used 62% of the sheet on this job.
In 30 s Nestbolt matches the competitors' 300 s result on 10 of 11 jobs. The first
final run (build 484ce8b) stopped with an error on one job; the fix is in 75cbb32
and both runs are published. Every run, including failures, is in
BENCHMARKS.md; status lists the evidence per
gate. The results page shows every
per-job number, tool revision, seed and the hardware; python scripts/reproduce.py
--phase final --final-acceptance rebuilds the datasets, reruns what is missing and regenerates it.
What works today
- **Import** SVG and DXF: lines, arcs, ellipses, Béziers, B-splines, blocks,
transforms and units, converted to millimetres. Each closed outline is a part;
outlines inside it are its holes. Choose cutting layers, identify stock outlines,