Claude Code – Claude Opus 5 (high) vs. Codex – GPT-6.1 Sol (high): geospatial agent comparison
Comparison between Claude Code – Claude Opus 5 (high) 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
| Metric | Claude Code – Claude Opus 5 (high) | Codex – GPT-6.1 Sol (high) |
|---|---|---|
| Geospatial Agent Index | 63* (partial: attempt 1 on 160 of 320 tasks) | 63* |
| Earth-Bench V2 score | 63 | 58 |
| GeoBenchX score | 62 | 67 |
| GeoAgentBench score (guided GIS workflow; outside the index) | 100 | 100 |
| GeoAnalystBench score (guided GIS workflow; outside the index) | 100 | 100 |
| Raster and remote sensing score | 62 | 54 |
| Vector and overlay score | No data | 50 |
| Networks and routing score | No data | No data |
| Climate and time series score | 65 | 66 |
| Spatial statistics and interpolation score | 50 | 29 |
| Mapping and cartography score | 87 | 78 |
| Recognising infeasible requests score | 50 | 67 |
| Cost per task | $0.522 | $0.081 |
| Time per task | 2.3 min | 1.8 min |
| Tokens per attempt | 253k | 149k |
| Turns per attempt | 9.1 | 7.8 |
| Attempts decided | 160 | 320 |
| Input price per 1M tokens | $5.00 | $2.00 |
| Output price per 1M tokens | $25.00 | $10.00 |
| Context window | No data | No data |
| Image input | No data | No data |
| Developer | Anthropic | OpenAI |
Charts
Partial coverage. Claude Code – Claude Opus 5 (high): 112 of 147 Earth-Bench V2 tasks; 48 of 173 GeoBenchX tasks. Grey placeholders identify these entries in the index, cost and time 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
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) |
|---|---|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 63* | No pending judgements; coverage incomplete | 2 of 2 | 320 of 614 planned attempts |
Cost per task
Average cost per task (USD) · Lower is better
First eight selected entries in metric order. Full results in table view.
How to read this chart
Not shown: partial coverage. Claude Code – Claude Opus 5 (high).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | $0.081 | 320 of 614 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.
How to read this chart
Not shown: partial coverage. Claude Code – Claude Opus 5 (high).
Data table: Time per task
| Model | Creator | Time per task | Coverage (attempts) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 1.8 min | 320 of 614 planned attempts |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Claude Code – Claude Opus 5 (high) or Codex – GPT-6.1 Sol (high)?
Which is cheaper per task, Claude Code – Claude Opus 5 (high) or Codex – GPT-6.1 Sol (high)?
Which is faster per task, Claude Code – Claude Opus 5 (high) or Codex – GPT-6.1 Sol (high)?
Which has the larger context window, Claude Code – Claude Opus 5 (high) or Codex – GPT-6.1 Sol (high)?
More: Claude Code – Claude Opus 5 (high) · Codex – GPT-6.1 Sol (high) · all comparisons
