Spatial 3D geometric reasoning and multi-part assembly benchmark administered by Epoch AI.
34 model results
One row per model and compatible score measure. Mean = equal-weight arithmetic average of imported reports. Distinct configurations reported for the same model in a source table remain separate. Reports can overlap; the range is not a confidence interval. Unbundle to inspect each observation.
Epoch AI public data snapshot, CC BY 4.0. Evaluation run by Epoch AI. CSV: furniture_assembly.csv; score column: Best score (across scorers); fraction scale: 1. Model version is retained in configuration. This column selects the best score across published scorers, rather than an average across scorers. Original source authors retain credit and any additional licensing terms.
TRACE THE SCORE · Per-model notes use published breakdowns where available.
Score vs. release date
Epoch AI · 34 observations
Furniture Assembly · Best score (across scorers) · % · higher is better
Dates are model release dates recorded by Epoch AI, not evaluation dates. Each point retains its published score and configuration. Separate releases are not a matched longitudinal experiment. Missing dates are omitted. Explore all reported results ↓
The dashed line traces the best observed score through the model release dates. It describes this selection of reports, with their original configurations. It does not estimate unmeasured models or costs.
View plotted values and sources (34)
Furniture Assembly Benchmark · Furniture Assembly · Best score (across scorers) · %. Published measurements in their original score units.
Spatial 3D geometric reasoning and multi-part assembly benchmark administered by Epoch AI.
Reading the measurement
Ask whether the evaluation rewards recalling a fact, constructing a model, running an experiment or supporting a discovery. Those tasks require different evidence. For research claims, inspect reproducibility, uncertainty and what was actually checked.
Evidence status
Catalogued from the supplied benchmark research notes. Publisher directories, where linked, are discovery references. Numerical model results are shown only when a source dataset has been imported; a catalog entry alone does not establish an independently reviewed evaluation.
Epoch data and evaluation setting
Epoch AI publishes this benchmark in its capability collection. Imported rows retain the published score column and model configuration. Original authors and evaluation providers remain credited in the result references.
Epoch attribution and score coverage
Data is attributed to Epoch AI under CC BY 4.0, with original evaluation providers credited in the linked source snapshots. Scores are imported only where a published mapping identifies the field and its scale; missing or incompatible records are omitted rather than assigned zero.
Where this fits in an evaluation suite
A correct multiple-choice answer and a supported scientific contribution demand different evidence. Check whether the score rewards a proposal, an executed experiment, or a completed research target.
Start with a capability hypothesis, then choose a second test with a different failure mode. Keep the checkpoint, reasoning effort, agent tools, sampling policy, and scoring procedure fixed when measuring a training intervention. Record failures and missing outputs in the denominator.
A reproducible comparison
Record the source publication, benchmark version, scoring units, denominator, tool access and attempt budget. Preserve uncertainty and distinguish developer-reported results from independent evaluations.
Publish the exact run configuration, item coverage, score units, and available uncertainty. If a source supplies only an aggregate or a single run, preserve that limit. A new model name or a rounded score alone does not establish a capability improvement.