Codex – GPT-6.1 Sol (high) vs. Codex – GPT-6 Luna (xhigh): geospatial agent comparison
Comparison between Codex – GPT-6.1 Sol (high) 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 | Codex – GPT-6.1 Sol (high) | Codex – GPT-6 Luna (xhigh) |
|---|---|---|
| Geospatial Agent Index | 80* (partial: 2.8 of 3 attempts) | 77* (partial: 1.9 of 3 attempts) |
| GeoAgentBench score | 100 | 99 |
| GeoBenchX score | 66 | 60 |
| Earth-Bench score | 53 | 55 |
| GeoAnalystBench score | 100 | 95 |
| Raster and remote sensing score | 72 | 75 |
| Vector and overlay score | 78 | 78 |
| Networks and routing score | 100 | 100 |
| Climate and time series score | 76 | 75 |
| Spatial statistics and interpolation score | 61 | 63 |
| Mapping and cartography score | 76 | 64 |
| Recognising infeasible requests score | 68 | 62 |
| Cost per task | $0.080 | $0.0092 |
| Time per task | 1.8 min | 3.4 min |
| Tokens per attempt | 143k | 236k |
| Turns per attempt | 7.8 | 9.8 |
| Attempts decided | 753 | 512 |
| Input price per 1M tokens | $2.00 | $0.10 |
| Output price per 1M tokens | $10.00 | $0.50 |
| Context window | No data | No data |
| Image input | No data | No data |
| Developer | OpenAI | 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) |
|---|---|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 80* (partial: 2.8 of 3 attempts) | 72 to 80 | 4 of 4 | 753 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 |
Codex – GPT-6.1 Sol (high)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) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | $0.080 | 813 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) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 1.8 min | 813 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, Codex – GPT-6.1 Sol (high) or Codex – GPT-6 Luna (xhigh)?
- Codex – GPT-6.1 Sol (high), at 80 against 77 for Codex – GPT-6 Luna (xhigh). Codex – GPT-6.1 Sol (high): 753 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, Codex – GPT-6.1 Sol (high) or Codex – GPT-6 Luna (xhigh)?
- Codex – GPT-6 Luna (xhigh), at $0.0092 against $0.080 for Codex – GPT-6.1 Sol (high).
- Which is faster per task, Codex – GPT-6.1 Sol (high) or Codex – GPT-6 Luna (xhigh)?
- Codex – GPT-6.1 Sol (high), at 1.8 min against 3.4 min for Codex – GPT-6 Luna (xhigh).
- Which has the larger context window, Codex – GPT-6.1 Sol (high) or Codex – GPT-6 Luna (xhigh)?
- Not known yet: Codex – GPT-6.1 Sol (high) has no context window data and Codex – GPT-6 Luna (xhigh) has no context window data.
More: Codex – GPT-6.1 Sol (high) · Codex – GPT-6 Luna (xhigh) · all comparisons