Claude Code – GLM-5.2 (max) vs. Codex – gpt-oss-20b (high): geospatial agent comparison

Comparison between Claude Code – GLM-5.2 (max) and Codex – gpt-oss-20b (high) on the Geospatial Agent Index, each benchmark, cost, time and token use, from the same tasks, agent and limits. Methodology.

Side by side

Claude Code – GLM-5.2 (max) vs. Codex – gpt-oss-20b (high)
Metric	Claude Code – GLM-5.2 (max)	Codex – gpt-oss-20b (high)
Geospatial Agent Index	66* (partial: attempt 1 on 550 of 565 tasks)	4* (partial: attempt 1 on 173 of 565 tasks)
Earth-Bench V2 score	64	0
GeoBenchX score	58	8
GS-QA2 score	76	No data
GeoAgentBench score (guided GIS workflow; outside the index)	No data	No data
GeoAnalystBench score (guided GIS workflow; outside the index)	No data	No data
Raster and remote sensing score	73	0
Vector and overlay score	71	25
Networks and routing score	No data	No data
Climate and time series score	67	0
Spatial statistics and interpolation score	43	0
Mapping and cartography score	81	4
Recognising infeasible requests score	41	12
Cost per task	$0.373	$0.140
Time per task	6.2 min	8.0 min
Tokens per attempt	651k	683k
Turns per attempt	15.8	29.5
Attempts decided	550	170
Input price per 1M tokens	$1.40	$0.20
Output price per 1M tokens	$4.40	$0.30
Context window	262,144	128,000
Image input	No	No
Developer	Z.ai	OpenAI

Charts

Partial coverage. Claude Code – GLM-5.2 (max): 140 of 147 Earth-Bench V2 tasks; 165 of 173 GeoBenchX tasks; Codex – gpt-oss-20b (high): 32 of 147 Earth-Bench V2 tasks; 141 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

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. Claude Code – GLM-5.2 (max), Codex – gpt-oss-20b (high).

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. Claude Code – GLM-5.2 (max), Codex – gpt-oss-20b (high).

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, Claude Code – GLM-5.2 (max) or Codex – gpt-oss-20b (high)?

Not comparable yet: Claude Code – GLM-5.2 (max) has partial coverage (140 of 147 Earth-Bench V2 tasks; 165 of 173 GeoBenchX tasks) and Codex – gpt-oss-20b (high) has partial coverage (32 of 147 Earth-Bench V2 tasks; 141 of 173 GeoBenchX tasks; GS-QA2 incomplete), so it is not ranked. Claude Code – GLM-5.2 (max): 550 of 859 planned attempts (15 excluded). Codex – gpt-oss-20b (high): 170 of 614 planned attempts. Coverage is partial; scores can change as more attempts are decided.

Which is cheaper per task, Claude Code – GLM-5.2 (max) or Codex – gpt-oss-20b (high)?

Codex – gpt-oss-20b (high), at $0.140 against $0.373 for Claude Code – GLM-5.2 (max).

Which writes fewer output tokens per task, Claude Code – GLM-5.2 (max) or Codex – gpt-oss-20b (high)?

Codex – gpt-oss-20b (high), at 29k against 30k for Claude Code – GLM-5.2 (max).

Which has the larger context window, Claude Code – GLM-5.2 (max) or Codex – gpt-oss-20b (high)?

Claude Code – GLM-5.2 (max), at 262,144 tokens against 128,000 tokens for Codex – gpt-oss-20b (high).

More: Claude Code – GLM-5.2 (max) · Codex – gpt-oss-20b (high) · all comparisons