Terminus-2 – GLM-5.3-Flash (max) vs. Codex – GPT-6 Luna (low): geospatial agent comparison

Comparison between Terminus-2 – GLM-5.3-Flash (max) 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

Terminus-2 – GLM-5.3-Flash (max) vs. Codex – GPT-6 Luna (low)
Metric	Terminus-2 – GLM-5.3-Flash (max)	Codex – GPT-6 Luna (low)
Geospatial Agent Index	64* (partial: attempt 1 on 467 of 488 tasks)	51* (partial: attempt 1 on 449 of 488 tasks)
Earth-Bench V2 score	51	44
GeoBenchX score	57	50
GS-QA2 score	84	59
GeoAgentBench score (guided GIS workflow; outside the index)	84	92
GeoAnalystBench score (guided GIS workflow; outside the index)	84	79
Raster and remote sensing score	72	55
Vector and overlay score	86	57
Climate and time series score	51	49
Spatial statistics and interpolation score	38	38
Mapping and cartography score	67	71
Recognising infeasible requests score	48	30
Cost per task	$0.088	$0.0031
Time per task	21.5 min	1.4 min
Tokens per attempt	770k	114k
Turns per attempt	15.1	7.8
Attempts decided	467	449
Input price per 1M tokens	$0.15	$0.10
Output price per 1M tokens	$0.50	$0.50
Context window	1,048,576	No data
Image input	Yes	No data
Developer	Z.ai	OpenAI

Charts

Partial coverage. Terminus-2 – GLM-5.3-Flash (max): 200 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, Terminus-2 – GLM-5.3-Flash (max) or Codex – GPT-6 Luna (low)?

Not comparable yet: Terminus-2 – GLM-5.3-Flash (max) has partial coverage (200 of 221 GS-QA2 tasks) and Codex – GPT-6 Luna (low) has partial coverage (111 of 150 GeoBenchX tasks), so it is not ranked. Terminus-2 – GLM-5.3-Flash (max): 467 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, Terminus-2 – GLM-5.3-Flash (max) or Codex – GPT-6 Luna (low)?

Codex – GPT-6 Luna (low), at $0.0031 against $0.088 for Terminus-2 – GLM-5.3-Flash (max).

Which writes fewer output tokens per task, Terminus-2 – GLM-5.3-Flash (max) or Codex – GPT-6 Luna (low)?

Codex – GPT-6 Luna (low), at 1k against 28k for Terminus-2 – GLM-5.3-Flash (max).

Which has the larger context window, Terminus-2 – GLM-5.3-Flash (max) or Codex – GPT-6 Luna (low)?

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

More: Terminus-2 – GLM-5.3-Flash (max) · Codex – GPT-6 Luna (low) · all comparisons