Codex – gpt-oss-120b (high) vs. Claude Code – Claude Opus 4.8 (high): geospatial agent comparison
Comparison between Codex – gpt-oss-120b (high) and Claude Code – Claude Opus 4.8 (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 | Codex – gpt-oss-120b (high) | Claude Code – Claude Opus 4.8 (high) |
|---|---|---|
| Geospatial Agent Index | 47* (partial: attempt 1 on 49 of 565 tasks) | 67* (partial: attempt 1 on 498 of 565 tasks) |
| Earth-Bench V2 score | 62 | 59 |
| GeoBenchX score | 31 | 65 |
| GS-QA2 score | No data | 77 |
| GeoAgentBench score (guided GIS workflow; outside the index) | No data | 97 |
| GeoAnalystBench score (guided GIS workflow; outside the index) | No data | 100 |
| Raster and remote sensing score | 64 | 74 |
| Vector and overlay score | No data | 71 |
| Networks and routing score | No data | No data |
| Climate and time series score | 0 | 64 |
| Spatial statistics and interpolation score | 0 | 31 |
| Mapping and cartography score | 44 | 81 |
| Recognising infeasible requests score | 25 | 55 |
| Cost per task | $0.236 | $0.290 |
| Time per task | 12.4 min | 1.3 min |
| Tokens per attempt | 642k | 140k |
| Turns per attempt | 29.7 | 6.4 |
| Attempts decided | 44 | 498 |
| Input price per 1M tokens | $0.35 | $5.00 |
| Output price per 1M tokens | $0.75 | $25.00 |
| Context window | 128,000 | No data |
| Image input | No | No data |
| Developer | OpenAI | Anthropic |
Charts
Partial coverage. Codex – gpt-oss-120b (high): 8 of 147 Earth-Bench V2 tasks; 41 of 173 GeoBenchX tasks; GS-QA2 incomplete; Claude Code – Claude Opus 4.8 (high): 135 of 147 Earth-Bench V2 tasks; 119 of 173 GeoBenchX tasks; 244 of 245 GS-QA2 tasks. 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
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) |
|---|
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. Codex – gpt-oss-120b (high), Claude Code – Claude Opus 4.8 (high).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|
Output tokens per task
Average output tokens per attempt, reasoning included · Lower is better
First eight selected entries in metric order. Full results in table view.
How to read this chart
Not shown: partial coverage. Codex – gpt-oss-120b (high), Claude Code – Claude Opus 4.8 (high).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Codex – gpt-oss-120b (high) or Claude Code – Claude Opus 4.8 (high)?
Which is cheaper per task, Codex – gpt-oss-120b (high) or Claude Code – Claude Opus 4.8 (high)?
Which writes fewer output tokens per task, Codex – gpt-oss-120b (high) or Claude Code – Claude Opus 4.8 (high)?
Which has the larger context window, Codex – gpt-oss-120b (high) or Claude Code – Claude Opus 4.8 (high)?
More: Codex – gpt-oss-120b (high) · Claude Code – Claude Opus 4.8 (high) · all comparisons