Terminus-2 – GLM-4.7-Flash (Reasoning) vs. Terminus-2 – gpt-oss-120b (high): geospatial agent comparison
Comparison between Terminus-2 – GLM-4.7-Flash (Reasoning) and Terminus-2 – gpt-oss-120b (high) 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 – GLM-4.7-Flash (Reasoning) | Terminus-2 – gpt-oss-120b (high) |
|---|---|---|
| Geospatial Agent Index | 43* | 53* |
| GeoAgentBench score | 36 | 70 |
| GeoBenchX score | 46 | 42 |
| Earth-Bench score | 48 | 46 |
| GeoAnalystBench score | 42 | 53 |
| Raster and remote sensing score | 39 | 52 |
| Vector and overlay score | 36 | 56 |
| Networks and routing score | 20 | 100 |
| Climate and time series score | 54 | 62 |
| Spatial statistics and interpolation score | 46 | 30 |
| Mapping and cartography score | 58 | 43 |
| Recognising infeasible requests score | 36 | 47 |
| Cost per task | $0.025 | $0.026 |
| Time per task | 9.5 min | 4.6 min |
| Tokens per attempt | 332k | 59k |
| Turns per attempt | 15.8 | 5.3 |
| Attempts decided | 143 | 249 |
| Input price per 1M tokens | $0.06 | $0.35 |
| Output price per 1M tokens | $0.40 | $0.75 |
| Context window | 131,072 | 128,000 |
| Image input | No | No |
| Developer | Z.ai | OpenAI |
Charts
Axis Spatial Geospatial Agent Index
Equal-weight average of the evaluation scores, 0 to 100 · Higher is better
Data table: Axis Spatial Geospatial Agent Index
| Model | Creator | Geospatial Agent Index | Range while attempts are pending | Benchmarks covered | Coverage (attempts) |
|---|---|---|---|---|---|
| Terminus-2 – gpt-oss-120b (high) | OpenAI | 53* | No pending judgements; coverage incomplete | 4 of 4 | 249 of 870 planned attempts |
| Terminus-2 – GLM-4.7-Flash (Reasoning) | Z.ai | 43* | 43 to 44 | 4 of 4 | 143 of 870 planned attempts |
Cost per task
Average cost per task (USD) · Lower is better
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – GLM-4.7-Flash (Reasoning) | Z.ai | $0.025 | 144 of 870 planned attempts |
| Terminus-2 – gpt-oss-120b (high) | OpenAI | $0.026 | 249 of 870 planned attempts |
Time per task
Average agent wall time per task · Lower is better
Data table: Time per task
| Model | Creator | Time per task | Coverage (attempts) |
|---|---|---|---|
| Terminus-2 – GLM-4.7-Flash (Reasoning) | Z.ai | 9.5 min | 144 of 870 planned attempts |
| Terminus-2 – gpt-oss-120b (high) | OpenAI | 4.6 min | 249 of 870 planned attempts |
Frequently asked questions
- Which scores higher on the Geospatial Agent Index, Terminus-2 – GLM-4.7-Flash (Reasoning) or Terminus-2 – gpt-oss-120b (high)?
- Terminus-2 – gpt-oss-120b (high), at 53 against 43 for Terminus-2 – GLM-4.7-Flash (Reasoning). Terminus-2 – GLM-4.7-Flash (Reasoning): 143 of 870 planned attempts. Terminus-2 – gpt-oss-120b (high): 249 of 870 planned attempts. Coverage is partial; scores can change as more attempts are decided.
- Which is cheaper per task, Terminus-2 – GLM-4.7-Flash (Reasoning) or Terminus-2 – gpt-oss-120b (high)?
- Terminus-2 – GLM-4.7-Flash (Reasoning), at $0.025 against $0.026 for Terminus-2 – gpt-oss-120b (high).
- Which is faster per task, Terminus-2 – GLM-4.7-Flash (Reasoning) or Terminus-2 – gpt-oss-120b (high)?
- Terminus-2 – gpt-oss-120b (high), at 4.6 min against 9.5 min for Terminus-2 – GLM-4.7-Flash (Reasoning).
- Which has the larger context window, Terminus-2 – GLM-4.7-Flash (Reasoning) or Terminus-2 – gpt-oss-120b (high)?
- Terminus-2 – GLM-4.7-Flash (Reasoning), at 131,072 tokens against 128,000 tokens for Terminus-2 – gpt-oss-120b (high).
More: Terminus-2 – GLM-4.7-Flash (Reasoning) · Terminus-2 – gpt-oss-120b (high) · all comparisons