Claude Code – GLM-5.2 (max) vs. Codex – GPT-6.1 Sol (high): geospatial agent comparison

Comparison between Claude Code – GLM-5.2 (max) and Codex – GPT-6.1 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

Claude Code – GLM-5.2 (max) vs. Codex – GPT-6.1 Sol (high)
Metric	Claude Code – GLM-5.2 (max)	Codex – GPT-6.1 Sol (high)
Geospatial Agent Index	53* (partial: attempt 1 on 200 of 565 tasks)	70*
Earth-Bench V2 score	63	58
GeoBenchX score	42	67
GS-QA2 score	No data	84
GeoAgentBench score (guided GIS workflow; outside the index)	No data	100
GeoAnalystBench score (guided GIS workflow; outside the index)	No data	100
Raster and remote sensing score	62	73
Vector and overlay score	40	80
Networks and routing score	No data	No data
Climate and time series score	67	66
Spatial statistics and interpolation score	No data	29
Mapping and cartography score	No data	78
Recognising infeasible requests score	41	67
Cost per task	$0.437	$0.062
Time per task	7.1 min	1.4 min
Tokens per attempt	827k	116k
Turns per attempt	18.7	6.8
Attempts decided	120	565
Input price per 1M tokens	$1.40	$2.00
Output price per 1M tokens	$4.40	$10.00
Context window	262,144	No data
Image input	No	No data
Developer	Z.ai	OpenAI

Charts

Partial coverage. Claude Code – GLM-5.2 (max): 35 of 147 Earth-Bench V2 tasks; 165 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

Planned attempts still to come

Data table: Geospatial Agent Index

Geospatial Agent Index
Model	Creator	Geospatial Agent Index	Range while attempts are pending	Benchmarks covered	Coverage (attempts)
Codex – GPT-6.1 Sol (high)	OpenAI	70*	No pending judgements; coverage incomplete; 207 results awaiting review	3 of 3	565 of 859 planned attempts (1 excluded)

Cost per task

Average cost per task (USD) · Lower is better

Planned attempts still to come

How to read this chart

Not shown: partial coverage. Claude Code – GLM-5.2 (max).

Data table: Cost per task

Cost per task
Model	Creator	Cost per task	Coverage (attempts)
Codex – GPT-6.1 Sol (high)	OpenAI	$0.062	565 of 859 planned attempts (1 excluded)

Output tokens per task

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

Planned attempts still to come

How to read this chart

Not shown: partial coverage. Claude Code – GLM-5.2 (max).

Data table: Output tokens per task

Output tokens per task
Model	Creator	Output tokens per task	Coverage (attempts)
Codex – GPT-6.1 Sol (high)	OpenAI	2k	565 of 859 planned attempts (1 excluded)

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Claude Code – GLM-5.2 (max) or Codex – GPT-6.1 Sol (high)?

Not comparable yet: Claude Code – GLM-5.2 (max) has partial coverage (35 of 147 Earth-Bench V2 tasks; 165 of 173 GeoBenchX tasks; GS-QA2 incomplete), so it is not ranked. Claude Code – GLM-5.2 (max): 120 of 614 planned attempts (9 excluded). Codex – GPT-6.1 Sol (high): 565 of 859 planned attempts (1 excluded). 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-6.1 Sol (high)?

Codex – GPT-6.1 Sol (high), at $0.062 against $0.437 for Claude Code – GLM-5.2 (max).

Which writes fewer output tokens per task, Claude Code – GLM-5.2 (max) or Codex – GPT-6.1 Sol (high)?

Codex – GPT-6.1 Sol (high), at 2k against 34k for Claude Code – GLM-5.2 (max).

Which has the larger context window, Claude Code – GLM-5.2 (max) or Codex – GPT-6.1 Sol (high)?

Not known yet: Codex – GPT-6.1 Sol (high) has no context window data.

More: Claude Code – GLM-5.2 (max) · Codex – GPT-6.1 Sol (high) · all comparisons