Terminus-2 – GLM-4.7-Flash (thinking on) vs. Codex – GPT-6.1 Sol (xhigh): geospatial agent comparison
Comparison between Terminus-2 – GLM-4.7-Flash (thinking on) and Codex – GPT-6.1 Sol (xhigh) 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 (xhigh) |
|---|---|---|
| Geospatial Agent Index | 40 | 78* (partial: 2 of 3 attempts) |
| GeoAgentBench score | 43 | 100 |
| GeoBenchX score | 39 | 64 |
| Earth-Bench score | 35 | 48 |
| GeoAnalystBench score | 42 | 100 |
| Raster and remote sensing score | 36 | 70 |
| Vector and overlay score | 46 | 78 |
| Networks and routing score | 33 | 100 |
| Climate and time series score | 44 | 72 |
| Spatial statistics and interpolation score | 29 | 62 |
| Mapping and cartography score | 50 | 73 |
| Recognising infeasible requests score | 33 | 66 |
| Cost per task | $0.030 | $0.124 |
| Time per task | 9.2 min | 3.0 min |
| Tokens per attempt | 419k | 201k |
| Turns per attempt | 17.9 | 9.0 |
| Attempts decided | 870 | 551 |
| 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 (xhigh) | OpenAI | 78* (partial: 2 of 3 attempts) | 74 to 79 | 4 of 4 | 551 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 (xhigh)
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 (xhigh) | OpenAI | $0.124 | 591 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 (xhigh) | OpenAI | 3.0 min | 591 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 (xhigh)?
- Codex – GPT-6.1 Sol (xhigh), at 78 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 (xhigh): 551 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 (xhigh)?
- Terminus-2 – GLM-4.7-Flash (thinking on), at $0.030 against $0.124 for Codex – GPT-6.1 Sol (xhigh).
- Which is faster per task, Terminus-2 – GLM-4.7-Flash (thinking on) or Codex – GPT-6.1 Sol (xhigh)?
- Codex – GPT-6.1 Sol (xhigh), at 3.0 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 (xhigh)?
- Not known yet: Codex – GPT-6.1 Sol (xhigh) has no context window data.
More: Terminus-2 – GLM-4.7-Flash (thinking on) · Codex – GPT-6.1 Sol (xhigh) · all comparisons