Axis Spatial

Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 vs. GLM-4.7-Flash (Reasoning), Claude Code

Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 against GLM-4.7-Flash (Reasoning), 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 Nano Omni 30B (Reasoning), Terminus-2 vs. GLM-4.7-Flash (Reasoning), Claude Code
MetricNemotron 3 Nano Omni 30B (Reasoning), Terminus-2GLM-4.7-Flash (Reasoning), Claude Code
Geospatial Agent Index: Text only2041
Geospatial Agent Index: Text + visionNo dataNo image input
Earth-Bench V2 score2938
GeoBenchX score2139
GS-QA2 score948
Vision agents scoreNo dataNo image input
GeoAgentBench score (Guided workflows; not in the Agent Index)2630
GeoAnalystBench score (Guided workflows; not in the Agent Index)1626
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 score1741
GIS analysis score649
Climate and time series score2739
Spatial statistics score023
Making maps score1649
Recognising infeasible requests score3340
Cost per task$0.13$0.27
Time per task (at 100 output tokens/s)4.9 min3.8 min
Tokens per attempt589k1.34M
Turns per attempt30.737.8
Input price per 1M tokens$0.20$0.060
Output price per 1M tokens$0.80$0.40
Context window256,000131,072
Image inputYesNo
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-4.7-Flash (Reasoning), Claude Code: 41; Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2: 20025507510041GLM-4.7-Flash (Reasoning)20Nemotron 3 Nano Omni 30B (Reasoning)
Data table: Geospatial Agent Index
Geospatial Agent Index
ModelDeveloperGeospatial Agent Index
GLM-4.7-Flash (Reasoning), Claude CodeZ.ai41
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2NVIDIA20

Cost per task

Average cost per task (USD) · Lower is better

Cost per taskCost per task in US dollars: Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2: $0.13; GLM-4.7-Flash (Reasoning), Claude Code: $0.27$0$0.10$0.20$0.30$0.40$0.13Nemotron 3 Nano Omni 30B (Reasoning)$0.27GLM-4.7-Flash (Reasoning)
Data table: Cost per task
Cost per task
ModelDeveloperCost per task
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2NVIDIA$0.13
GLM-4.7-Flash (Reasoning), Claude CodeZ.ai$0.27

Output tokens per task

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

Output tokens per taskOutput tokens per task: GLM-4.7-Flash (Reasoning), Claude Code: 15k; Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2: 22k010k20k30k40k15kGLM-4.7-Flash (Reasoning)22kNemotron 3 Nano Omni 30B (Reasoning)
Data table: Output tokens per task
Output tokens per task
ModelDeveloperOutput tokens per task
GLM-4.7-Flash (Reasoning), Claude CodeZ.ai15k
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2NVIDIA22k

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
GLM-4.7-Flash (Reasoning), Claude Code, 41 to 20.
Which is cheaper per task, Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2, $0.13 to $0.27.
Which writes fewer output tokens per task, Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
GLM-4.7-Flash (Reasoning), Claude Code, 15k to 22k.
Which has the larger context window, Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2, 256,000 tokens to 131,072 tokens.

More: Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2 · GLM-4.7-Flash (Reasoning), Claude Code · All comparisons