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OptiCutter benchmark

This is a benchmark of OptiCutter against Cutlist Evolution, run on a mix of real-world and test projects.

We build Cutlist Evolution, which is a reason to read the numbers carefully rather than a reason to skip them. Each job below is published with its parts count, its stock, the yield and the sheet count, so you can compare it against what your current tool returns on work of the same shape.

Both tools produce sheet layouts and cover the basics of doing so. The table lists the features where the two diverge. Every one of them is present in Cutlist Evolution and absent from OptiCutter, and they are the ones that start to matter as jobs get more complex.

Feature OptiCutter Cutlist Evolution
Multiple materials and thicknesses
Offcut management
Cut measurements
Cost estimates
Saw settings
First cut direction choice
Share projects via link
Live chat support

Both tools were given the same parts and the same stock on two projects, one a deliberately hard test and one a real job at production scale. They are:

  1. One of our internal benchmarks: 39 shapes and a single stock item.
  2. A sizeable real-world project, two stock dimensions, 2,786 parts, unlimited stock.

A third section follows the two head-to-head tests. It measures the same engine against a fixed lower bound across eleven production jobs, which answers a question a two-job comparison cannot: whether the margin above is a pair of lucky results or how the optimizer behaves in general.

This is one of our internal tests: 39 shapes that have to fit onto a single stock item. It is a real challenge for most optimizers. OptiCutter fails to fit all the parts, so finishing the project means ordering a second sheet and doubling the material cost.

Tool Yield Sheets needed Material area
OptiCutter 49.1% 2 11.1 sq m
Cutlist Evolution 98.2% 1 5.6 sq m
Additional efficiency 49.1% 1 fewer stock 5.5 sq m less material

The yield column says the same thing from the other side. At 49.1%, more than half the material OptiCutter asks you to buy leaves the shop as offcut. Cutlist Evolution fits the job on one sheet at 98.2%.

2. Two stock dimensions and many parts for a construction project

Section titled “2. Two stock dimensions and many parts for a construction project”

A user came to us needing an estimate and a bill of materials for a large construction project. It ran to 2,786 parts, with two stock dimensions available. The larger of the two was a special order and the more expensive material, so the brief was to reduce how much of it the job required. The results are below.

Tool Yield Sheets needed Material area
OptiCutter 78% 1,176 42,080 sq ft
Cutlist Evolution 85% 1,125 38,664 sq ft
Additional efficiency 7% 51 fewer stock 3,416 sq ft less material

That is 51 fewer stock items ordered, worth thousands of dollars on a special-order material. A project this size needs a custom plan, but on a job carrying that many materials the software usually pays for itself the first time it runs.

3. Eleven production jobs against the theoretical limit

Section titled “3. Eleven production jobs against the theoretical limit”

The two tests above are head-to-head. This one is not, and it is worth being plain about that: OptiCutter was not part of this study. It measures Cutlist Evolution’s optimizer against the industrial packing tools Magi-Cut and Ardis, and against something more useful than either.

Every job was also scored against the fewest stock it could physically need, computed as a Dual First-Fit lower bound from the part areas. That number is not a target set by a vendor. It is a floor no optimizer can beat, which makes it the one benchmark figure nobody can tune towards.

Eleven of the hardest-packing jobs in our library, 1,136 parts in all, run with identical parts, stock, kerf and trim:

Tool Total stock used Mean yield Jobs at the limit
Magi-Cut 103 82.2%
Ardis 99 85.4%
Cutlist Evolution 94 90.3% 11 of 11
Fewest physically possible 94

The last two rows are the result. Across all eleven jobs Cutlist Evolution used 94 stock items, and 94 is the fewest the parts could occupy. On every job in the study it matched that floor, so on this set nothing could have done better. Each figure was re-run three times to confirm it.

Against the rivals that is 9 stock saved on Magi-Cut and 5 on Ardis over the same work, or 8.7% and 5.1% less material respectively. Job sizes ran from 64 to 170 parts on 2800 x 2050 mm stock, so this is production work rather than a contrived test.

The reason it belongs on this page is what it says about the two head-to-head results above. An optimizer that lands on the physical floor eleven times out of eleven is not winning those comparisons by luck on the day.

The full study, with every job’s layout viewable side by side, is at smartcut.dev/benchmarks.

Both are competent tools. On the two projects here Cutlist Evolution used less material, and the margin widened with the size and difficulty of the job: one sheet against two on the packing test, 1,125 sheets against 1,176 on the construction job. The eleven-job study points the same way from a different angle, landing on the fewest stock physically possible every time. The features in the table above, offcut management, cost estimates and the advanced settings among them, are what carry that difference into complex or large-scale work.

If you want a fuller run-through of either benchmark, or the same comparison run on your own parts list, get in touch. Which optimizer you choose is worth settling on measurements rather than on feature lists, including ours.