Codex – GPT-5.6 Luna (low): geospatial agent results

What this shows. The same attempts as the index, grouped by task format. Groups with few tasks are less certain. About these breakdowns.

What this shows. The same attempts as the index, grouped by kind of work. Groups with few tasks are less certain. About these breakdowns.

What this shows. The same attempts as the index, grouped by data type. Groups with few tasks are less certain. About these breakdowns.

What this shows. The same attempts as the index, grouped by task length. Groups with few tasks are less certain. About these breakdowns.

What this metric means. The equal-weight average of the 3 evaluation scores. Each evaluation score is the average pass@1 over that benchmark's tasks, from 0 to 100.

Partial coverage entries. An entry is ranked only when it has a first attempt on every task of every index component. Entries without that are marked partial coverage: they are listed apart with their coverage, for example "36 of 117 Earth-Bench V2 tasks", and are left out of the ranking, the index charts and the Pareto lines. An entry becomes ranked as soon as its first attempts are complete.

Coverage hatch. A hatched bar, and an asterisk in tables, marks an entry that does not yet have results for every scheduled attempt. While attempts await review, the table gives the range the score could still reach.

First attempt only. Scores currently use each entry's first attempt on every task. The full protocol is 3 attempts; averages over 3 will replace these once every entry has them. An entry without a first attempt on every task yet is marked "partial: attempt 1 on n of N tasks".

Partial coverage. Entries without a first attempt on every index task are not plotted; the table lists them. What is still running is on the models page.

What cost is measuring. What one attempt at a task would cost if paid token by token at the provider's published API prices, averaged over attempts: ordinary input tokens, input tokens served from the provider's cache at the lower cached price, tokens written to the cache where the provider charges for that, and output tokens (thinking included). Cost assumes each harness uses the model's pay-per-token API, priced at public list rates; sandboxes and our own engineering time are not included. Failed attempts count too.

How to read this chart. Each point is one model configuration. Further left means a lower average cost per task (log scale); higher means a higher Geospatial Agent Index. Both axes fit the models shown, so the score axis does not start at zero. The shaded most attractive quadrant is the top-left quarter of the plot, split at the middle of each axis: a reading aid that moves with the axes when you change the models shown, not a fixed bar. The dotted Pareto line joins the shown models that no cheaper shown model beats on score.