Axis Spatial

Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – GPT-5.6 Luna (medium): geospatial agent comparison

Comparison between Terminus-2 – GLM-4.7-Flash (thinking on) and Codex – GPT-5.6 Luna (medium) on the Geospatial Agent Index, each benchmark, cost, time and token use, from the same tasks, agent and limits. Methodology.

Side by side

Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – GPT-5.6 Luna (medium)
MetricTerminus-2 – GLM-4.7-Flash (thinking on)Codex – GPT-5.6 Luna (medium)
Geospatial Agent Index43* (partial: attempt 1 on 478 of 488 tasks)66* (partial: attempt 1 on 339 of 488 tasks)
Earth-Bench V2 score4460
GeoBenchX score4258
GS-QA2 score4479
GeoAgentBench score (guided GIS workflow; outside the index)4298
GeoAnalystBench score (guided GIS workflow; outside the index)37100
Raster and remote sensing score4378
Vector and overlay score4976
Climate and time series score4158
Spatial statistics and interpolation score150
Mapping and cartography score4783
Recognising infeasible requests score4341
Cost per task$0.036$0.0084
Time per task10.0 min2.1 min
Tokens per attempt520k125k
Turns per attempt26.08.9
Attempts decided478339
Input price per 1M tokens$0.060$0.20
Output price per 1M tokens$0.40$1.20
Context window131,072No data
Image inputNoNo data
DeveloperZ.aiOpenAI

Charts

Partial coverage. Terminus-2 – GLM-4.7-Flash (thinking on): 211 of 221 GS-QA2 tasks; Codex – GPT-5.6 Luna (medium): 107 of 117 Earth-Bench V2 tasks; 43 of 150 GeoBenchX tasks; 189 of 221 GS-QA2 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

Geospatial Agent IndexTerminus-2 – GLM-4.7-Flash (thinking on): Partial; Codex – GPT-5.6 Luna (medium): Partial0255075100PartialGLM-4.7-Flash (thinking on)PartialGPT-5.6 Luna (medium)
Data table: Geospatial Agent Index
Geospatial Agent Index
ModelCreatorGeospatial Agent IndexRange while attempts are pendingBenchmarks coveredCoverage (attempts)

Cost per task

Average cost per task (USD) · Lower is better

Cost per taskTerminus-2 – GLM-4.7-Flash (thinking on): Partial; Codex – GPT-5.6 Luna (medium): Partial$0$0.25$0.50$0.75$1.00PartialGLM-4.7-Flash (thinking on)PartialGPT-5.6 Luna (medium)
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
ModelCreatorCost per taskCoverage (attempts)

Output tokens per task

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

Output tokens per taskTerminus-2 – GLM-4.7-Flash (thinking on): Partial; Codex – GPT-5.6 Luna (medium): Partial00011PartialGLM-4.7-Flash (thinking on)PartialGPT-5.6 Luna (medium)
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
ModelCreatorOutput tokens per taskCoverage (attempts)

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-5.6 Luna (medium)?
Not comparable yet: Terminus-2 – GLM-4.7-Flash (thinking on) has partial coverage (211 of 221 GS-QA2 tasks) and 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), so it is not ranked. Terminus-2 – GLM-4.7-Flash (thinking on): 478 of 722 scheduled attempts (1 excluded). Codex – GPT-5.6 Luna (medium): 339 of 722 scheduled attempts. Coverage is partial; scores can change as more attempts are decided.
Which is cheaper per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-5.6 Luna (medium)?
Codex – GPT-5.6 Luna (medium), at $0.0084 against $0.036 for Terminus-2 – GLM-4.7-Flash (thinking on).
Which writes fewer output tokens per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-5.6 Luna (medium)?
Codex – GPT-5.6 Luna (medium), at 2k against 14k for Terminus-2 – GLM-4.7-Flash (thinking on).
Which has the larger context window, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-5.6 Luna (medium)?
Not known yet: Codex – GPT-5.6 Luna (medium) has no context window data.

More: Terminus-2 – GLM-4.7-Flash (thinking on) · Codex – GPT-5.6 Luna (medium) · all comparisons