Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – GPT-6.1 Sol (high): geospatial agent comparison
Comparison between Terminus-2 – GLM-4.7-Flash (thinking on) and Codex – GPT-6.1 Sol (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 (thinking on) | Codex – GPT-6.1 Sol (high) |
|---|---|---|
| Geospatial Agent Index | 40 | 80* (partial: 2.8 of 3 attempts) |
| GeoAgentBench score | 43 | 100 |
| GeoBenchX score | 39 | 66 |
| Earth-Bench score | 35 | 53 |
| GeoAnalystBench score | 42 | 100 |
| Raster and remote sensing score | 36 | 72 |
| Vector and overlay score | 46 | 78 |
| Networks and routing score | 33 | 100 |
| Climate and time series score | 44 | 76 |
| Spatial statistics and interpolation score | 29 | 61 |
| Mapping and cartography score | 50 | 76 |
| Recognising infeasible requests score | 33 | 68 |
| Cost per task | $0.030 | $0.080 |
| Time per task | 9.2 min | 1.8 min |
| Tokens per attempt | 419k | 143k |
| Turns per attempt | 17.9 | 7.8 |
| Attempts decided | 870 | 753 |
| Input price per 1M tokens | $0.06 | $2.00 |
| Output price per 1M tokens | $0.40 | $10.00 |
| Context window | 131,072 | No data |
| Image input | No | No data |
| Developer | Z.ai | 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 |
| Terminus-2 – GLM-4.7-Flash (thinking on) | Z.ai | 40 | No pending judgements | 4 of 4 | 870 of 870 planned attempts |
Codex – GPT-6.1 Sol (high)
Terminus-2 – GLM-4.7-Flash (thinking on)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) |
|---|---|---|---|
| Terminus-2 – GLM-4.7-Flash (thinking on) | Z.ai | $0.030 | 870 of 870 planned attempts |
| Codex – GPT-6.1 Sol (high) | OpenAI | $0.080 | 813 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) |
|---|---|---|---|
| Terminus-2 – GLM-4.7-Flash (thinking on) | Z.ai | 9.2 min | 870 of 870 planned attempts |
| Codex – GPT-6.1 Sol (high) | OpenAI | 1.8 min | 813 of 870 planned attempts |
Frequently asked questions
- Which scores higher on the Geospatial Agent Index, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-6.1 Sol (high)?
- Codex – GPT-6.1 Sol (high), at 80 against 40 for Terminus-2 – GLM-4.7-Flash (thinking on). Terminus-2 – GLM-4.7-Flash (thinking on): 870 of 870 planned attempts. Codex – GPT-6.1 Sol (high): 753 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 (thinking on) or Codex – GPT-6.1 Sol (high)?
- Terminus-2 – GLM-4.7-Flash (thinking on), at $0.030 against $0.080 for Codex – GPT-6.1 Sol (high).
- Which is faster per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-6.1 Sol (high)?
- Codex – GPT-6.1 Sol (high), at 1.8 min against 9.2 min for Terminus-2 – GLM-4.7-Flash (thinking on).
- Which has the larger context window, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-6.1 Sol (high)?
- Not known yet: Codex – GPT-6.1 Sol (high) has no context window data.
More: Terminus-2 – GLM-4.7-Flash (thinking on) · Codex – GPT-6.1 Sol (high) · all comparisons