Axis Spatial

Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – gpt-oss-120b (high): geospatial agent comparison

Comparison between Terminus-2 – GLM-4.7-Flash (thinking on) and Codex – gpt-oss-120b (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-oss-120b (high)
MetricTerminus-2 – GLM-4.7-Flash (thinking on)Codex – gpt-oss-120b (high)
Geospatial Agent Index39* (partial: attempt 1 on 555 of 565 tasks)47* (partial: attempt 1 on 49 of 565 tasks)
Earth-Bench V2 score3762
GeoBenchX score3731
GS-QA2 score43No data
GeoAgentBench score (guided GIS workflow; outside the index)42No data
GeoAnalystBench score (guided GIS workflow; outside the index)37No data
Raster and remote sensing score3864
Vector and overlay score46No data
Networks and routing scoreNo dataNo data
Climate and time series score370
Spatial statistics and interpolation score140
Mapping and cartography score4644
Recognising infeasible requests score3425
Cost per task$0.038$0.236
Time per task10.7 min12.4 min
Tokens per attempt548k642k
Turns per attempt26.229.7
Attempts decided55544
Input price per 1M tokens$0.06$0.35
Output price per 1M tokens$0.40$0.75
Context window131,072128,000
Image inputNoNo
DeveloperZ.aiOpenAI

Charts

Partial coverage. Terminus-2 – GLM-4.7-Flash (thinking on): 235 of 245 GS-QA2 tasks; Codex – gpt-oss-120b (high): 8 of 147 Earth-Bench V2 tasks; 41 of 173 GeoBenchX tasks; GS-QA2 incomplete. 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-oss-120b (high): Partial0255075100PartialGLM-4.7-Flash (thinking on)Partialgpt-oss-120b (high)
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-oss-120b (high): Partial$0$0.250$0.500$0.750$1.00PartialGLM-4.7-Flash (thinking on)Partialgpt-oss-120b (high)
How to read this chart

Not shown: partial coverage. Terminus-2 – GLM-4.7-Flash (thinking on), Codex – gpt-oss-120b (high).

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-oss-120b (high): Partial00011PartialGLM-4.7-Flash (thinking on)Partialgpt-oss-120b (high)
How to read this chart

Not shown: partial coverage. Terminus-2 – GLM-4.7-Flash (thinking on), Codex – gpt-oss-120b (high).

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-oss-120b (high)?
Not comparable yet: Terminus-2 – GLM-4.7-Flash (thinking on) has partial coverage (235 of 245 GS-QA2 tasks) and Codex – gpt-oss-120b (high) has partial coverage (8 of 147 Earth-Bench V2 tasks; 41 of 173 GeoBenchX tasks; GS-QA2 incomplete), so it is not ranked. Terminus-2 – GLM-4.7-Flash (thinking on): 555 of 859 planned attempts (1 excluded). Codex – gpt-oss-120b (high): 44 of 614 planned 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-oss-120b (high)?
Terminus-2 – GLM-4.7-Flash (thinking on), at $0.038 against $0.236 for Codex – gpt-oss-120b (high).
Which writes fewer output tokens per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – gpt-oss-120b (high)?
Terminus-2 – GLM-4.7-Flash (thinking on), at 15k against 29k for Codex – gpt-oss-120b (high).
Which has the larger context window, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – gpt-oss-120b (high)?
Terminus-2 – GLM-4.7-Flash (thinking on), at 131,072 tokens against 128,000 tokens for Codex – gpt-oss-120b (high).

More: Terminus-2 – GLM-4.7-Flash (thinking on) · Codex – gpt-oss-120b (high) · all comparisons