Terminus-2 – gpt-oss-120b (high) vs. Claude Code – GLM-5.3-Flash (max): geospatial agent comparison
Comparison between Terminus-2 – gpt-oss-120b (high) and Claude Code – GLM-5.3-Flash (max) 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 (high) | Claude Code – GLM-5.3-Flash (max) |
|---|---|---|
| Geospatial Agent Index | 39* | 41* (partial: attempt 1 on 135 of 565 tasks) |
| Earth-Bench V2 score | 43 | 43 |
| GeoBenchX score | 39 | 38 |
| GS-QA2 score | 37 | No data |
| GeoAgentBench score (guided GIS workflow; outside the index) | 70 | No data |
| GeoAnalystBench score (guided GIS workflow; outside the index) | 53 | No data |
| Raster and remote sensing score | 39 | 44 |
| Vector and overlay score | 35 | 50 |
| Networks and routing score | No data | No data |
| Climate and time series score | 46 | 67 |
| Spatial statistics and interpolation score | 14 | 0 |
| Mapping and cartography score | 39 | 0 |
| Recognising infeasible requests score | 44 | 44 |
| Cost per task | $0.032 | $0.139 |
| Time per task | 5.6 min | 18.3 min |
| Tokens per attempt | 72k | 1.26M |
| Turns per attempt | 6.3 | 25.9 |
| Attempts decided | 565 | 89 |
| Input price per 1M tokens | $0.35 | $0.15 |
| Output price per 1M tokens | $0.75 | $0.50 |
| Context window | 128,000 | 1,048,576 |
| Image input | No | Yes |
| Developer | OpenAI | Z.ai |
Charts
Partial coverage. Claude Code – GLM-5.3-Flash (max): 21 of 147 Earth-Bench V2 tasks; 114 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 (high) | OpenAI | 39* | No pending judgements; coverage incomplete; 90 results awaiting review; 2 trace reviews declined by the judge | 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-5.3-Flash (max).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – gpt-oss-120b (high) | OpenAI | $0.032 | 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-5.3-Flash (max).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – gpt-oss-120b (high) | OpenAI | 17k | 565 of 859 planned attempts |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Terminus-2 – gpt-oss-120b (high) or Claude Code – GLM-5.3-Flash (max)?
Which is cheaper per task, Terminus-2 – gpt-oss-120b (high) or Claude Code – GLM-5.3-Flash (max)?
Which writes fewer output tokens per task, Terminus-2 – gpt-oss-120b (high) or Claude Code – GLM-5.3-Flash (max)?
Which has the larger context window, Terminus-2 – gpt-oss-120b (high) or Claude Code – GLM-5.3-Flash (max)?
More: Terminus-2 – gpt-oss-120b (high) · Claude Code – GLM-5.3-Flash (max) · all comparisons