Claude Code – Claude Opus 5.5 (medium) vs. Codex – GPT-6 Luna (xhigh): geospatial agent comparison
Comparison between Claude Code – Claude Opus 5.5 (medium) 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
| Metric | Claude Code – Claude Opus 5.5 (medium) | Codex – GPT-6 Luna (xhigh) |
|---|---|---|
| Geospatial Agent Index | 81* (partial: 1.8 of 3 attempts) | 77* (partial: 1.9 of 3 attempts) |
| GeoAgentBench score | 96 | 99 |
| GeoBenchX score | 66 | 60 |
| Earth-Bench score | 62 | 55 |
| GeoAnalystBench score | 100 | 95 |
| Raster and remote sensing score | 76 | 75 |
| Vector and overlay score | 83 | 78 |
| Networks and routing score | 100 | 100 |
| Climate and time series score | 85 | 75 |
| Spatial statistics and interpolation score | 69 | 63 |
| Mapping and cartography score | 75 | 64 |
| Recognising infeasible requests score | 60 | 62 |
| Cost per task | $0.138 | $0.0092 |
| Time per task | 0.7 min | 3.4 min |
| Tokens per attempt | 103k | 236k |
| Turns per attempt | 4.9 | 9.8 |
| Attempts decided | 461 | 512 |
| Input price per 1M tokens | $4.00 | $0.10 |
| Output price per 1M tokens | $20.00 | $0.50 |
| Context window | No data | No data |
| Image input | No data | No data |
| Developer | Anthropic | OpenAI |
Charts
Geospatial Agent Index
Equal-weight average of the evaluation scores, 0 to 100 · Higher is better
First eight selected entries in metric order. Full results in table view.
Data table: Geospatial Agent Index
| Model | Creator | Geospatial Agent Index | Range while attempts are pending | Benchmarks covered | Coverage (attempts) |
|---|---|---|---|---|---|
| Claude Code – Claude Opus 5.5 (medium) | Anthropic | 81* (partial: 1.8 of 3 attempts) | 70 to 81 | 4 of 4 | 461 of 870 planned attempts |
| Codex – GPT-6 Luna (xhigh) | OpenAI | 77* (partial: 1.9 of 3 attempts) | 72 to 78 | 4 of 4 | 512 of 870 planned attempts |
Claude Code – Claude Opus 5.5 (medium)
Codex – GPT-6 Luna (xhigh)Cost per task
Average cost per task (USD) · Lower is better
First eight selected entries in metric order. Full results in table view.
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Claude Code – Claude Opus 5.5 (medium) | Anthropic | $0.138 | 532 of 870 planned attempts |
| Codex – GPT-6 Luna (xhigh) | OpenAI | $0.0092 | 560 of 870 planned attempts |
Time per task
Average agent wall time per task · Lower is better
First eight selected entries in metric order. Full results in table view.
Data table: Time per task
| Model | Creator | Time per task | Coverage (attempts) |
|---|---|---|---|
| Claude Code – Claude Opus 5.5 (medium) | Anthropic | 0.7 min | 532 of 870 planned attempts |
| Codex – GPT-6 Luna (xhigh) | OpenAI | 3.4 min | 560 of 870 planned attempts |
Frequently asked questions
- Which scores higher on the Geospatial Agent Index, Claude Code – Claude Opus 5.5 (medium) or Codex – GPT-6 Luna (xhigh)?
- Claude Code – Claude Opus 5.5 (medium), at 81 against 77 for Codex – GPT-6 Luna (xhigh). Claude Code – Claude Opus 5.5 (medium): 461 of 870 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 Opus 5.5 (medium) or Codex – GPT-6 Luna (xhigh)?
- Codex – GPT-6 Luna (xhigh), at $0.0092 against $0.138 for Claude Code – Claude Opus 5.5 (medium).
- Which is faster per task, Claude Code – Claude Opus 5.5 (medium) or Codex – GPT-6 Luna (xhigh)?
- Claude Code – Claude Opus 5.5 (medium), at 0.7 min against 3.4 min for Codex – GPT-6 Luna (xhigh).
- Which has the larger context window, Claude Code – Claude Opus 5.5 (medium) or Codex – GPT-6 Luna (xhigh)?
- Not known yet: Claude Code – Claude Opus 5.5 (medium) has no context window data and Codex – GPT-6 Luna (xhigh) has no context window data.
More: Claude Code – Claude Opus 5.5 (medium) · Codex – GPT-6 Luna (xhigh) · all comparisons