AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

Claire Radar

CADWorld

A computer-use agent must leave a valid, editable FreeCAD project—not merely a plausible screenshot.

September 2026 paper v1 and the authors’ public task site; the main experiment uses GUI interaction.

What work does it cover?

There are 200 tasks across 11 workflows, including sketches, parts, assemblies, CAM, FEM and technical drawings. The suite is largest in part modelling and sketching; small categories should be read with their task counts.

Authors’ project · tasks, evaluation and reproduction links

How the agent works

The main setup permits screenshots and GUI actions, with 100 GUI steps per task. A separate terminal experiment uses 50 tasks and should not be pooled with these results.

Authors’ project · tasks, evaluation and reproduction links · CADWorld introducing paper · protocol, evaluation and limitations (arXiv v1)

The saved artifact decides success

Executable checks inspect native .FCStd projects and required auxiliary files. Geometry, constraints, feature structure or downstream outputs must satisfy every task requirement; diagnostics do not award partial credit.

CADWorld introducing paper · protocol, evaluation and limitations (arXiv v1)

What the published comparison shows

The best reported agent succeeds on 17.5% of tasks, versus an 87.0% expert reference. The expert row represents one reference pass, not a study of average engineer performance.

Authors’ project · tasks, evaluation and reproduction links

What remains outside the test

Tasks provide explicit goals and assets. FreeCAD-only results do not establish performance in other CAD products, open-ended client projects, or requirements discovery.

CADWorld introducing paper · protocol, evaluation and limitations (arXiv v1)

Start from a task and its checks

The official site links the tasks, VM and installation guide. Reproduction needs Linux, KVM, Docker and the FreeCAD VM; preserve the harness, budget and trace alongside each reported result.

Authors’ project · tasks, evaluation and reproduction links

Published task-success results

Success requires all task checks to pass. These are the success values from Table 3, distinct from its finish, cost and action-count columns.

Paper Table 3 · success column, full 200-task GUI experiment
Agent / referenceTask success
GPT5.4 (CUA)17.5%
Opus4.8 (CUA)16.0%
Kimi K2.67.5%
OpenCUA1.5%
Holo 3.10.5%
Qwen3.60.0%
MiniMax M30.0%
Human Expert reference87.0%

Names and percentages follow the paper. The human row is a single expert reference pass; it is not an average across engineers. The terminal-only 50-task ablation is excluded.

CADWorld introducing paper · protocol, evaluation and limitations (arXiv v1)

Evidence available for this benchmark

The guide reproduces the paper's result tables with their separate tasks and metrics; these tables have not been added to normalized score data.

Start with these resources

Cited documents and dates (1)

Catalog collected on 2026-10-14; resources and fields reflect that saved source.

Recorded attention

Observed on: 2026-10-11

Hugging Face paper upvotes
14

View source snapshot

Dated attention observations, not live counts or benchmark scores.

Evaluation context and evidence

Source
Claire Radar
Publisher
Not recorded
Benchmark release
2026-09-14
Collected
2026-10-14
Modality
Not recorded

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Paper results 1

The guide above contains the paper's tables, retaining tasks, units, denominators and citations.