Codex – GPT-5.6 Luna (medium) vs. Codex – GPT-6 Luna (low): geospatial agent comparison

Comparison between Codex – GPT-5.6 Luna (medium) and Codex – GPT-6 Luna (low) on the Geospatial Agent Index, each benchmark, cost, time and token use, from the same tasks, agent and limits. Methodology.

Side by side

Codex – GPT-5.6 Luna (medium) vs. Codex – GPT-6 Luna (low)
Metric	Codex – GPT-5.6 Luna (medium)	Codex – GPT-6 Luna (low)
Geospatial Agent Index	66* (partial: attempt 1 on 339 of 488 tasks)	51* (partial: attempt 1 on 449 of 488 tasks)
Earth-Bench V2 score	60	44
GeoBenchX score	58	50
GS-QA2 score	79	59
GeoAgentBench score (guided GIS workflow; outside the index)	98	92
GeoAnalystBench score (guided GIS workflow; outside the index)	100	79
Raster and remote sensing score	78	55
Vector and overlay score	76	57
Climate and time series score	58	49
Spatial statistics and interpolation score	0	38
Mapping and cartography score	83	71
Recognising infeasible requests score	41	30
Cost per task	$0.0084	$0.0031
Time per task	2.1 min	1.4 min
Tokens per attempt	125k	114k
Turns per attempt	8.9	7.8
Attempts decided	339	449
Input price per 1M tokens	$0.20	$0.10
Output price per 1M tokens	$1.20	$0.50
Context window	No data	No data
Image input	No data	No data
Developer	OpenAI	OpenAI

Charts

Partial coverage. Codex – GPT-5.6 Luna (medium): 107 of 117 Earth-Bench V2 tasks; 43 of 150 GeoBenchX tasks; 189 of 221 GS-QA2 tasks; Codex – GPT-6 Luna (low): 111 of 150 GeoBenchX tasks. Grey placeholders identify these entries in the index, cost and output token charts; their height does not represent a value. Comparable bars appear when first-attempt coverage is complete. Their available results remain in the side-by-side table.

Geospatial Agent Index

Equal-weight average of the evaluation scores, 0 to 100 · Higher is better

Data table: Geospatial Agent Index

Geospatial Agent Index
Model	Creator	Geospatial Agent Index	Range while attempts are pending	Benchmarks covered	Coverage (attempts)

Cost per task

Average cost per task (USD) · Lower is better

How to read this chart

Not shown: partial coverage. 2 entries without a first attempt on every index task. What is still running is on the models page.

Data table: Cost per task

Cost per task
Model	Creator	Cost per task	Coverage (attempts)

Output tokens per task

Average output tokens per attempt, reasoning included · Lower is better

How to read this chart

Not shown: partial coverage. 2 entries without a first attempt on every index task. What is still running is on the models page.

Data table: Output tokens per task

Output tokens per task
Model	Creator	Output tokens per task	Coverage (attempts)

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Codex – GPT-5.6 Luna (medium) or Codex – GPT-6 Luna (low)?

Not comparable yet: Codex – GPT-5.6 Luna (medium) has partial coverage (107 of 117 Earth-Bench V2 tasks; 43 of 150 GeoBenchX tasks; 189 of 221 GS-QA2 tasks) and Codex – GPT-6 Luna (low) has partial coverage (111 of 150 GeoBenchX tasks), so it is not ranked. Codex – GPT-5.6 Luna (medium): 339 of 722 scheduled attempts. Codex – GPT-6 Luna (low): 449 of 722 scheduled attempts. Coverage is partial; scores can change as more attempts are decided.

Which is cheaper per task, Codex – GPT-5.6 Luna (medium) or Codex – GPT-6 Luna (low)?

Codex – GPT-6 Luna (low), at $0.0031 against $0.0084 for Codex – GPT-5.6 Luna (medium).

Which writes fewer output tokens per task, Codex – GPT-5.6 Luna (medium) or Codex – GPT-6 Luna (low)?

Codex – GPT-6 Luna (low), at 1k against 2k for Codex – GPT-5.6 Luna (medium).

Which has the larger context window, Codex – GPT-5.6 Luna (medium) or Codex – GPT-6 Luna (low)?

Not known yet: Codex – GPT-5.6 Luna (medium) has no context window data and Codex – GPT-6 Luna (low) has no context window data.

More: Codex – GPT-5.6 Luna (medium) · Codex – GPT-6 Luna (low) · all comparisons