gpt-oss-120b (low) vs Laguna XS 2.1 (Reasoning)
Results updated 8 November 2026 · Both in Terminus-2 · How we benchmark
Verdict
Laguna XS 2.1 (Reasoning) beats gpt-oss-120b (low) by 6 points; gpt-oss-120b (low) is cheaper and faster.
- Cost per task
- $0.0046 vs $0.054
- Time per task
- 0.5 min vs 17.3 min
- Tokens per attempt
- 11k vs 937k
- Image input
- No vs No
gpt-oss-120b (low), Terminus-2 scores higher on GeoBenchX; Laguna XS 2.1 (Reasoning), Terminus-2 scores higher on Earth-Bench V2 and GS-QA2. gpt-oss-120b (low), Terminus-2 is cheaper and faster: $0.0046 against $0.054 per task, and 0.5 min against 17.3 min.
Where they differ most
By kind of work, share of tasks passed, 0 to 100 · Higher is better
| Kind of work | gpt-oss-120b (low) | Laguna XS 2.1 (Reasoning) |
|---|---|---|
| Making maps | 21 | 53 |
| Remote sensing and raster analysis | 24 | 39 |
| Change detection | 36 | 48 |
| Climate and time series | 26 | 36 |
Where the tasks are set: each kind of work links to its tasks and scoresCharts for each: gpt-oss-120b (low), Terminus-2 · Laguna XS 2.1 (Reasoning), Terminus-2.
Side by side
| Metric | gpt-oss-120b (low), Terminus-2 | Laguna XS 2.1 (Reasoning), Terminus-2 |
|---|---|---|
| Geospatial Agent Index: Text only | 31 | 37 |
| Geospatial Agent Index: Text + vision | No image input | No data |
| Earth-Bench V2 score | 28 | 44 |
| GeoBenchX score | 37 | 33 |
| GS-QA2 score | 29 | 35 |
| Vision agents score | No image input | No data |
| GeoAgentBench score (Guided workflows; not in the Agent Index) | 60 | 63 |
| GeoAnalystBench score (Guided workflows; not in the Agent Index) | 47 | 63 |
| OGD4All score (standalone; in no index) | No data | 65 |
| GeoNatureAgent score (standalone; in no index) | No data | 36 |
| MultiGlobeQA score (standalone; in no index) | No data | 59 |
| GeoAgentEval score (standalone; in no index) | No data | 60 |
| ImpactMesh score (standalone; in no index) | No data | No data |
| Remote sensing and raster analysis score | 24 | 39 |
| Change detection score | 36 | 48 |
| GIS analysis score | 34 | 35 |
| Climate and time series score | 26 | 36 |
| Making maps score | 21 | 53 |
| Cost per task | $0.0046 | $0.054 |
| Time per task (at 100 output tokens/s) | 0.5 min | 17.3 min |
| Tokens per attempt | 11k | 937k |
| Turns per attempt | 2.9 | 36.7 |
| Input price per 1M tokens | $0.15 | $0.10 |
| Output price per 1M tokens | $0.59 | $0.20 |
| Context window | 128,000 | 262,144 |
| Image input | No | No |
| Developer | OpenAI | Poolside |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, gpt-oss-120b (low), Terminus-2 or Laguna XS 2.1 (Reasoning), Terminus-2?
Laguna XS 2.1 (Reasoning), Terminus-2, 37 to 31.
Which is cheaper per task, gpt-oss-120b (low), Terminus-2 or Laguna XS 2.1 (Reasoning), Terminus-2?
gpt-oss-120b (low), Terminus-2, $0.0046 to $0.054.
Which writes fewer output tokens per task, gpt-oss-120b (low), Terminus-2 or Laguna XS 2.1 (Reasoning), Terminus-2?
gpt-oss-120b (low), Terminus-2, 2k to 24k.
Which has the larger context window, gpt-oss-120b (low), Terminus-2 or Laguna XS 2.1 (Reasoning), Terminus-2?
Laguna XS 2.1 (Reasoning), Terminus-2, 262,144 tokens to 128,000 tokens.