Axis Spatial

Claude Code – Claude Haiku 5.5 (xhigh) vs. Codex – GPT-6 Luna (xhigh): geospatial agent comparison

Comparison between Claude Code – Claude Haiku 5.5 (xhigh) and Codex – GPT-6 Luna (xhigh) 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 – Claude Haiku 5.5 (xhigh) vs. Codex – GPT-6 Luna (xhigh)
MetricClaude Code – Claude Haiku 5.5 (xhigh)Codex – GPT-6 Luna (xhigh)
Geospatial Agent Index78 (partial: 1 of 3 attempts)77* (partial: 1.9 of 3 attempts)
GeoAgentBench score10099
GeoBenchX score6560
Earth-Bench score5255
GeoAnalystBench score9595
Raster and remote sensing score7375
Vector and overlay score7878
Networks and routing score100100
Climate and time series score7175
Spatial statistics and interpolation score6263
Mapping and cartography score7464
Recognising infeasible requests score6562
Cost per task$0.023$0.0092
Time per task1.9 min3.4 min
Tokens per attempt635k236k
Turns per attempt12.09.8
Attempts decided290512
Input price per 1M tokens$0.10$0.10
Output price per 1M tokens$0.50$0.50
Context windowNo dataNo data
Image inputNo dataNo data
DeveloperAnthropicOpenAI

Charts

Geospatial Agent Index

Equal-weight average of the evaluation scores, 0 to 100 · Higher is better

  • Partial coverage
Geospatial Agent IndexClaude Code – Claude Haiku 5.5 (xhigh): 78; Codex – GPT-6 Luna (xhigh): 77* (partial coverage)025507510078Claude Haiku 5.5 (xhigh)77*GPT-6 Luna (xhigh)
Data table: Geospatial Agent Index
Geospatial Agent Index
ModelCreatorGeospatial Agent IndexRange while attempts are pendingBenchmarks coveredCoverage (attempts)
Claude Code – Claude Haiku 5.5 (xhigh)Anthropic78 (partial: 1 of 3 attempts)No pending judgements4 of 4290 of 290 planned attempts
Codex – GPT-6 Luna (xhigh)OpenAI77* (partial: 1.9 of 3 attempts)72 to 784 of 4512 of 870 planned attempts

Cost per task

Average cost per task (USD) · Lower is better

  • Partial coverage
Cost per taskCodex – GPT-6 Luna (xhigh): $0.0092 (partial coverage); Claude Code – Claude Haiku 5.5 (xhigh): $0.023$0$0.0063$0.013$0.019$0.025$0.0092GPT-6 Luna (xhigh)$0.023Claude Haiku 5.5 (xhigh)
Data table: Cost per task
Cost per task
ModelCreatorCost per taskCoverage (attempts)
Claude Code – Claude Haiku 5.5 (xhigh)Anthropic$0.023290 of 290 planned attempts
Codex – GPT-6 Luna (xhigh)OpenAI$0.0092560 of 870 planned attempts

Time per task

Average agent wall time per task · Lower is better

  • Partial coverage
Time per taskClaude Code – Claude Haiku 5.5 (xhigh): 1.9 min; Codex – GPT-6 Luna (xhigh): 3.4 min (partial coverage)0m1m2m3m4m1.9 minClaude Haiku 5.5 (xhigh)3.4 minGPT-6 Luna (xhigh)
Data table: Time per task
Time per task
ModelCreatorTime per taskCoverage (attempts)
Claude Code – Claude Haiku 5.5 (xhigh)Anthropic1.9 min290 of 290 planned attempts
Codex – GPT-6 Luna (xhigh)OpenAI3.4 min560 of 870 planned attempts

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Claude Code – Claude Haiku 5.5 (xhigh) or Codex – GPT-6 Luna (xhigh)?
Claude Code – Claude Haiku 5.5 (xhigh), at 78 against 77 for Codex – GPT-6 Luna (xhigh). Claude Code – Claude Haiku 5.5 (xhigh): 290 of 290 planned attempts. Codex – GPT-6 Luna (xhigh): 512 of 870 planned attempts. Coverage is partial; scores can change as more attempts are decided.
Which is cheaper per task, Claude Code – Claude Haiku 5.5 (xhigh) or Codex – GPT-6 Luna (xhigh)?
Codex – GPT-6 Luna (xhigh), at $0.0092 against $0.023 for Claude Code – Claude Haiku 5.5 (xhigh).
Which is faster per task, Claude Code – Claude Haiku 5.5 (xhigh) or Codex – GPT-6 Luna (xhigh)?
Claude Code – Claude Haiku 5.5 (xhigh), at 1.9 min against 3.4 min for Codex – GPT-6 Luna (xhigh).
Which has the larger context window, Claude Code – Claude Haiku 5.5 (xhigh) or Codex – GPT-6 Luna (xhigh)?
Not known yet: Claude Code – Claude Haiku 5.5 (xhigh) has no context window data and Codex – GPT-6 Luna (xhigh) has no context window data.

More: Claude Code – Claude Haiku 5.5 (xhigh) · Codex – GPT-6 Luna (xhigh) · all comparisons