Axis Spatial

Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 vs. GLM-5.2 (max), Claude Code

Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 against GLM-5.2 (max), Claude Code: Geospatial Agent Index, each evaluation, cost, time and tokens, on the same tasks and limits. The harnesses differ, so part of any gap can come from the harness. Methodology.

Side by side

Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 vs. GLM-5.2 (max), Claude Code
MetricNemotron 3.5 Lightning 30B (Reasoning), Terminus-2GLM-5.2 (max), Claude Code
Geospatial Agent Index: Text only1173
Geospatial Agent Index: Text + visionNo dataNo image input
Earth-Bench V2 score1671
GeoBenchX score1266
GS-QA2 score483
Vision agents scoreNo dataNo image input
GeoAgentBench score (Guided workflows; not in the Agent Index)10No data
GeoAnalystBench score (Guided workflows; not in the Agent Index)32No data
OGD4All score (standalone; in no index)No dataNo data
GeoNatureAgent score (standalone; in no index)No dataNo data
MultiGlobeQA score (standalone; in no index)No dataNo data
GeoAgentEval score (standalone; in no index)No dataNo data
Remote sensing and raster analysis score1180
GIS analysis score781
Climate and time series score1572
Spatial statistics score046
Making maps score784
Recognising infeasible requests score1252
Cost per task$0.012$0.34
Time per task (at 100 output tokens/s)4.9 min6.3 min
Tokens per attempt249k617k
Turns per attempt17.315.4
Input price per 1M tokens$0.070$1.40
Output price per 1M tokens$0.20$4.40
Context window262,144262,144
Image inputNoNo
DeveloperNVIDIAZ.ai

Charts

Geospatial Agent Index

Equal average of Earth-Bench V2, GeoBenchX and GS-QA2, 0 to 100 · Higher is better

Geospatial Agent IndexScores 0 to 100: GLM-5.2 (max), Claude Code: 73; Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2: 11025507510073GLM-5.2 (max)11Nemotron 3.5 Lightning 30B (Reasoning)
Data table: Geospatial Agent Index
Geospatial Agent Index
ModelDeveloperGeospatial Agent Index
GLM-5.2 (max), Claude CodeZ.ai73
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2NVIDIA11

Cost per task

Average cost per task (USD) · Lower is better

Cost per taskCost per task in US dollars: Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2: $0.012; GLM-5.2 (max), Claude Code: $0.34$0$0.10$0.20$0.30$0.40$0.012Nemotron 3.5 Lightning 30B (Reasoning)$0.34GLM-5.2 (max)
Data table: Cost per task
Cost per task
ModelDeveloperCost per task
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2NVIDIA$0.012
GLM-5.2 (max), Claude CodeZ.ai$0.34

Output tokens per task

Average output tokens per attempt, reasoning included · Lower is better

Output tokens per taskOutput tokens per task: Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2: 6k; GLM-5.2 (max), Claude Code: 28k010k20k30k40k6kNemotron 3.5 Lightning 30B (Reasoning)28kGLM-5.2 (max)
Data table: Output tokens per task
Output tokens per task
ModelDeveloperOutput tokens per task
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2NVIDIA6k
GLM-5.2 (max), Claude CodeZ.ai28k

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or GLM-5.2 (max), Claude Code?
GLM-5.2 (max), Claude Code, 73 to 11.
Which is cheaper per task, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or GLM-5.2 (max), Claude Code?
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2, $0.012 to $0.34.
Which writes fewer output tokens per task, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or GLM-5.2 (max), Claude Code?
Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2, 6k to 28k.
Which has the larger context window, Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 or GLM-5.2 (max), Claude Code?
They are level, at 262,144 tokens.

More: Nemotron 3.5 Lightning 30B (Reasoning), Terminus-2 · GLM-5.2 (max), Claude Code · All comparisons