Terminus-2 – Kimi K2.6 (always on) vs. Codex – GPT-5.6 Luna (medium): geospatial agent comparison
Comparison between Terminus-2 – Kimi K2.6 (always on) and Codex – GPT-5.6 Luna (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 | Terminus-2 – Kimi K2.6 (always on) | Codex – GPT-5.6 Luna (medium) |
|---|---|---|
| Geospatial Agent Index | 70* (partial: attempt 1 on 485 of 488 tasks) | 66* (partial: attempt 1 on 339 of 488 tasks) |
| Earth-Bench V2 score | 68 | 60 |
| GeoBenchX score | 64 | 58 |
| GS-QA2 score | 77 | 79 |
| GeoAgentBench score (guided GIS workflow; outside the index) | 90 | 98 |
| GeoAnalystBench score (guided GIS workflow; outside the index) | 79 | 100 |
| Raster and remote sensing score | 77 | 78 |
| Vector and overlay score | 74 | 76 |
| Climate and time series score | 69 | 58 |
| Spatial statistics and interpolation score | 15 | 0 |
| Mapping and cartography score | 77 | 83 |
| Recognising infeasible requests score | 57 | 41 |
| Cost per task | $0.089 | $0.0084 |
| Time per task | 8.0 min | 2.1 min |
| Tokens per attempt | 173k | 125k |
| Turns per attempt | 12.7 | 8.9 |
| Attempts decided | 485 | 339 |
| Input price per 1M tokens | $0.95 | $0.20 |
| Output price per 1M tokens | $4.00 | $1.20 |
| Context window | 262,144 | No data |
| Image input | Yes | No data |
| Developer | Moonshot AI | OpenAI |
Charts
Partial coverage. Terminus-2 – Kimi K2.6 (always on): 218 of 221 GS-QA2 tasks; Codex – GPT-5.6 Luna (medium): 107 of 117 Earth-Bench V2 tasks; 43 of 150 GeoBenchX tasks; 189 of 221 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. 2 entries without a first attempt on every index task. What is still running is on the models page.
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. 2 entries without a first attempt on every index task. What is still running is on the models page.
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, Terminus-2 – Kimi K2.6 (always on) or Codex – GPT-5.6 Luna (medium)?
Which is cheaper per task, Terminus-2 – Kimi K2.6 (always on) or Codex – GPT-5.6 Luna (medium)?
Which writes fewer output tokens per task, Terminus-2 – Kimi K2.6 (always on) or Codex – GPT-5.6 Luna (medium)?
Which has the larger context window, Terminus-2 – Kimi K2.6 (always on) or Codex – GPT-5.6 Luna (medium)?
More: Terminus-2 – Kimi K2.6 (always on) · Codex – GPT-5.6 Luna (medium) · all comparisons
