Axis Spatial

GLM-5.3 (low), Terminus-2 vs. Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2

GLM-5.3 (low), Terminus-2 against Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: Geospatial Agent Index, each evaluation, cost, time and tokens, on the same tasks and limits. Methodology.

Side by side

GLM-5.3 (low), Terminus-2 vs. Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2
MetricGLM-5.3 (low), Terminus-2Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2
Geospatial Agent Index: Text only6652
Geospatial Agent Index: Text + visionNo image inputNo data
Earth-Bench V2 score5746
GeoBenchX score6053
GS-QA2 score8059
Vision agents scoreNo image inputNo data
GeoAgentBench score (Guided workflows; not in the Agent Index)9268
GeoAnalystBench score (Guided workflows; not in the Agent Index)9537
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 score7461
GIS analysis score7551
Climate and time series score5946
Spatial statistics score2331
Making maps score7767
Recognising infeasible requests score5343
Cost per task$0.27$0.0096
Time per task (at 100 output tokens/s)2.7 min3.8 min
Tokens per attempt217k98k
Turns per attempt10.410.1
Input price per 1M tokens$1.40$0.15
Output price per 1M tokens$4.40$0.50
Context window1,048,576262,144
Image inputNoYes
DeveloperZ.aiNVIDIA

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-5.3 (low), Terminus-2: 66; Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: 52025507510066GLM-5.3 (low)52Nemotron 3.5 Super VL 120B (Reasoning)
Data table: Geospatial Agent Index
Geospatial Agent Index
ModelDeveloperGeospatial Agent Index
GLM-5.3 (low), Terminus-2Z.ai66
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2NVIDIA52

Cost per task

Average cost per task (USD) · Lower is better

Cost per taskCost per task in US dollars: Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: $0.0096; GLM-5.3 (low), Terminus-2: $0.27$0$0.10$0.20$0.30$0.40$0.0096Nemotron 3.5 Super VL 120B (Reasoning)$0.27GLM-5.3 (low)
Data table: Cost per task
Cost per task
ModelDeveloperCost per task
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2NVIDIA$0.0096
GLM-5.3 (low), Terminus-2Z.ai$0.27

Output tokens per task

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

Output tokens per taskOutput tokens per task: Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: 7k; GLM-5.3 (low), Terminus-2: 10k05k10k15k20k7kNemotron 3.5 Super VL 120B (Reasoning)10kGLM-5.3 (low)
Data table: Output tokens per task
Output tokens per task
ModelDeveloperOutput tokens per task
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2NVIDIA7k
GLM-5.3 (low), Terminus-2Z.ai10k

Frequently asked questions

Which scores higher on the Geospatial Agent Index, GLM-5.3 (low), Terminus-2 or Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2?
GLM-5.3 (low), Terminus-2, 66 to 52.
Which is cheaper per task, GLM-5.3 (low), Terminus-2 or Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2?
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2, $0.0096 to $0.27.
Which writes fewer output tokens per task, GLM-5.3 (low), Terminus-2 or Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2?
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2, 7k to 10k.
Which has the larger context window, GLM-5.3 (low), Terminus-2 or Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2?
GLM-5.3 (low), Terminus-2, 1,048,576 tokens to 262,144 tokens.

More: GLM-5.3 (low), Terminus-2 · Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2 · All comparisons