Codex – gpt-oss-120b (high) vs. Claude Code – Claude Sonnet 5.5 (medium): geospatial agent comparison
Comparison between Codex – gpt-oss-120b (high) and Claude Code – Claude Sonnet 5.5 (medium) 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 Sonnet 5.5 (medium) |
|---|---|---|
| Geospatial Agent Index | 47* (partial: attempt 1 on 49 of 565 tasks) | 63* |
| Earth-Bench V2 score | 62 | 49 |
| GeoBenchX score | 31 | 66 |
| GS-QA2 score | No data | 73 |
| GeoAgentBench score (guided GIS workflow; outside the index) | No data | 98 |
| GeoAnalystBench score (guided GIS workflow; outside the index) | No data | 95 |
| Raster and remote sensing score | 64 | 63 |
| Vector and overlay score | No data | 71 |
| Networks and routing score | No data | No data |
| Climate and time series score | 0 | 56 |
| Spatial statistics and interpolation score | 0 | 57 |
| Mapping and cartography score | 44 | 76 |
| Recognising infeasible requests score | 25 | 58 |
| Cost per task | $0.236 | $0.048 |
| Time per task | 12.4 min | 0.5 min |
| Tokens per attempt | 642k | 79k |
| Turns per attempt | 29.7 | 4.3 |
| Attempts decided | 44 | 565 |
| Input price per 1M tokens | $0.35 | $2.00 |
| Output price per 1M tokens | $0.75 | $10.00 |
| 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. 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) |
|---|---|---|---|---|---|
| Claude Code – Claude Sonnet 5.5 (medium) | Anthropic | 63* | No pending judgements; coverage incomplete; 178 results awaiting review | 3 of 3 | 565 of 859 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. Codex – gpt-oss-120b (high).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Claude Code – Claude Sonnet 5.5 (medium) | Anthropic | $0.048 | 565 of 859 planned 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).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|---|---|---|
| Claude Code – Claude Sonnet 5.5 (medium) | Anthropic | 1k | 565 of 859 planned attempts |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Codex – gpt-oss-120b (high) or Claude Code – Claude Sonnet 5.5 (medium)?
Which is cheaper per task, Codex – gpt-oss-120b (high) or Claude Code – Claude Sonnet 5.5 (medium)?
Which writes fewer output tokens per task, Codex – gpt-oss-120b (high) or Claude Code – Claude Sonnet 5.5 (medium)?
Which has the larger context window, Codex – gpt-oss-120b (high) or Claude Code – Claude Sonnet 5.5 (medium)?
More: Codex – gpt-oss-120b (high) · Claude Code – Claude Sonnet 5.5 (medium) · all comparisons