Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 vs. Qwen 3.8 27B (xhigh), Terminus-2
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 against Qwen 3.8 27B (xhigh), Terminus-2: Geospatial Agent Index, each evaluation, cost, time and tokens, on the same tasks and limits. Methodology.
Side by side
| Metric | Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 | Qwen 3.8 27B (xhigh), Terminus-2 |
|---|---|---|
| Geospatial Agent Index: Text only | 11 | 61 |
| Geospatial Agent Index: Text + vision | No data | No data |
| Earth-Bench V2 score | 16 | 44 |
| GeoBenchX score | 12 | 66 |
| GS-QA2 score | 4 | 74 |
| Vision agents score | No data | No data |
| GeoAgentBench score (Guided workflows; not in the Agent Index) | 10 | 60 |
| GeoAnalystBench score (Guided workflows; not in the Agent Index) | 32 | 89 |
| OGD4All score (standalone; in no index) | No data | No data |
| GeoNatureAgent score (standalone; in no index) | No data | No data |
| MultiGlobeQA score (standalone; in no index) | No data | No data |
| GeoAgentEval score (standalone; in no index) | No data | No data |
| Remote sensing and raster analysis score | 11 | 64 |
| GIS analysis score | 7 | 77 |
| Climate and time series score | 15 | 42 |
| Spatial statistics score | 0 | 69 |
| Making maps score | 7 | 68 |
| Recognising infeasible requests score | 12 | 57 |
| Cost per task | $0.012 | $0.10 |
| Time per task (at 100 output tokens/s) | 4.9 min | 7.3 min |
| Tokens per attempt | 249k | 335k |
| Turns per attempt | 17.3 | 14.8 |
| Input price per 1M tokens | $0.070 | $0.45 |
| Output price per 1M tokens | $0.20 | $3.20 |
| Context window | 262,144 | 262,144 |
| Image input | No | Yes |
| Developer | NVIDIA | Alibaba (Qwen) |
Charts
Geospatial Agent Index
Equal average of Earth-Bench V2, GeoBenchX and GS-QA2, 0 to 100 · Higher is better
Data table: Geospatial Agent Index
| Model | Developer | Geospatial Agent Index |
|---|---|---|
| Qwen 3.8 27B (xhigh), Terminus-2 | Alibaba (Qwen) | 61 |
| Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 | NVIDIA | 11 |
Cost per task
Average cost per task (USD) · Lower is better
Data table: Cost per task
| Model | Developer | Cost per task |
|---|---|---|
| Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 | NVIDIA | $0.012 |
| Qwen 3.8 27B (xhigh), Terminus-2 | Alibaba (Qwen) | $0.10 |
Output tokens per task
Average output tokens per attempt, reasoning included · Lower is better
Data table: Output tokens per task
| Model | Developer | Output tokens per task |
|---|---|---|
| Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 | NVIDIA | 6k |
| Qwen 3.8 27B (xhigh), Terminus-2 | Alibaba (Qwen) | 19k |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or Qwen 3.8 27B (xhigh), Terminus-2?
Qwen 3.8 27B (xhigh), Terminus-2, 61 to 11.
Which is cheaper per task, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or Qwen 3.8 27B (xhigh), Terminus-2?
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2, $0.012 to $0.10.
Which writes fewer output tokens per task, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or Qwen 3.8 27B (xhigh), Terminus-2?
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2, 6k to 19k.
Which has the larger context window, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or Qwen 3.8 27B (xhigh), Terminus-2?
They are level, at 262,144 tokens.
More: Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 · Qwen 3.8 27B (xhigh), Terminus-2 · All comparisons
