Terminus-2 – gpt-oss-120b (low) vs. Claude Code – GLM-4.7-Flash (thinking on): geospatial agent comparison
Comparison between Terminus-2 – gpt-oss-120b (low) and Claude Code – GLM-4.7-Flash (thinking on) 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 – gpt-oss-120b (low) | Claude Code – GLM-4.7-Flash (thinking on) |
|---|---|---|
| Geospatial Agent Index | 28* | 27* (partial: attempt 1 on 52 of 565 tasks) |
| Earth-Bench V2 score | 24 | 20 |
| GeoBenchX score | 32 | 33 |
| GS-QA2 score | 27 | No data |
| GeoAgentBench score (guided GIS workflow; outside the index) | 60 | No data |
| GeoAnalystBench score (guided GIS workflow; outside the index) | 47 | No data |
| Raster and remote sensing score | 22 | 15 |
| Vector and overlay score | 31 | No data |
| Networks and routing score | No data | No data |
| Climate and time series score | 26 | 0 |
| Spatial statistics and interpolation score | 7 | 20 |
| Mapping and cartography score | 20 | 64 |
| Recognising infeasible requests score | 47 | 26 |
| Cost per task | $0.0048 | $0.089 |
| Time per task | 0.7 min | 13.6 min |
| Tokens per attempt | 12k | 1.37M |
| Turns per attempt | 2.9 | 35.5 |
| Attempts decided | 565 | 49 |
| Input price per 1M tokens | $0.35 | $0.06 |
| Output price per 1M tokens | $0.75 | $0.40 |
| Context window | 128,000 | 131,072 |
| Image input | No | No |
| Developer | OpenAI | Z.ai |
Charts
Partial coverage. Claude Code – GLM-4.7-Flash (thinking on): 10 of 147 Earth-Bench V2 tasks; 42 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) |
|---|---|---|---|---|---|
| Terminus-2 – gpt-oss-120b (low) | OpenAI | 28* | No pending judgements; coverage incomplete; 65 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. Claude Code – GLM-4.7-Flash (thinking on).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – gpt-oss-120b (low) | OpenAI | $0.0048 | 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. Claude Code – GLM-4.7-Flash (thinking on).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – gpt-oss-120b (low) | OpenAI | 2k | 565 of 859 planned attempts |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Terminus-2 – gpt-oss-120b (low) or Claude Code – GLM-4.7-Flash (thinking on)?
Which is cheaper per task, Terminus-2 – gpt-oss-120b (low) or Claude Code – GLM-4.7-Flash (thinking on)?
Which writes fewer output tokens per task, Terminus-2 – gpt-oss-120b (low) or Claude Code – GLM-4.7-Flash (thinking on)?
Which has the larger context window, Terminus-2 – gpt-oss-120b (low) or Claude Code – GLM-4.7-Flash (thinking on)?
More: Terminus-2 – gpt-oss-120b (low) · Claude Code – GLM-4.7-Flash (thinking on) · all comparisons