Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – GPT-6 Sol (high): geospatial agent comparison

Comparison between Terminus-2 – GLM-4.7-Flash (thinking on) and Codex – GPT-6 Sol (high) 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-6 Sol (high)
Metric	Terminus-2 – GLM-4.7-Flash (thinking on)	Codex – GPT-6 Sol (high)
Geospatial Agent Index	43* (partial: attempt 1 on 478 of 488 tasks)	80* (partial: attempt 1 on 475 of 488 tasks)
Earth-Bench V2 score	44	76
GeoBenchX score	42	75
GS-QA2 score	44	89
GeoAgentBench score (guided GIS workflow; outside the index)	42	100
GeoAnalystBench score (guided GIS workflow; outside the index)	37	100
Raster and remote sensing score	43	84
Vector and overlay score	49	86
Climate and time series score	41	80
Spatial statistics and interpolation score	15	33
Mapping and cartography score	47	85
Recognising infeasible requests score	43	79
Cost per task	$0.036	$0.080
Time per task	10.0 min	1.7 min
Tokens per attempt	520k	144k
Turns per attempt	26.0	8.6
Attempts decided	478	460
Input price per 1M tokens	$0.060	$2.00
Output price per 1M tokens	$0.40	$10.00
Context window	131,072	No data
Image input	No	No data
Developer	Z.ai	OpenAI

Charts

Partial coverage. Terminus-2 – GLM-4.7-Flash (thinking on): 211 of 221 GS-QA2 tasks; Codex – GPT-6 Sol (high): 116 of 117 Earth-Bench V2 tasks; 138 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-4.7-Flash (thinking on) or Codex – GPT-6 Sol (high)?

Not comparable yet: Terminus-2 – GLM-4.7-Flash (thinking on) has partial coverage (211 of 221 GS-QA2 tasks) and Codex – GPT-6 Sol (high) has partial coverage (116 of 117 Earth-Bench V2 tasks; 138 of 150 GeoBenchX tasks), so it is not ranked. Terminus-2 – GLM-4.7-Flash (thinking on): 478 of 722 scheduled attempts (1 excluded). Codex – GPT-6 Sol (high): 460 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-6 Sol (high)?

Terminus-2 – GLM-4.7-Flash (thinking on), at $0.036 against $0.080 for Codex – GPT-6 Sol (high).

Which writes fewer output tokens per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-6 Sol (high)?

Codex – GPT-6 Sol (high), at 3k 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-6 Sol (high)?

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

More: Terminus-2 – GLM-4.7-Flash (thinking on) · Codex – GPT-6 Sol (high) · all comparisons