Terminus-2 – DeepSeek V4 Flash (max) vs. Codex – GPT-5.6 Luna (high): geospatial agent comparison

Comparison between Terminus-2 – DeepSeek V4 Flash (max) and Codex – GPT-5.6 Luna (high) on the Geospatial Agent Index, each benchmark, cost, time and token use, from the same tasks, agent and limits. Methodology.

Side by side

Terminus-2 – DeepSeek V4 Flash (max) vs. Codex – GPT-5.6 Luna (high)
Metric	Terminus-2 – DeepSeek V4 Flash (max)	Codex – GPT-5.6 Luna (high)
Geospatial Agent Index	69*	84* (partial: attempt 1 on 46 of 488 tasks)
Earth-Bench V2 score	66	No data
GeoBenchX score	62	No data
GS-QA2 score	80	84
GeoAgentBench score (guided GIS workflow; outside the index)	96	No data
GeoAnalystBench score (guided GIS workflow; outside the index)	95	No data
Raster and remote sensing score	78	82
Vector and overlay score	75	100
Climate and time series score	66	No data
Spatial statistics and interpolation score	23	No data
Mapping and cartography score	79	No data
Recognising infeasible requests score	53	No data
Cost per task	$0.061	$0.0083
Time per task	9.3 min	1.7 min
Tokens per attempt	301k	126k
Turns per attempt	14.4	9.4
Attempts decided	486	46
Input price per 1M tokens	$0.44	$0.20
Output price per 1M tokens	$1.32	$1.20
Context window	1,048,576	No data
Image input	No	No data
Developer	DeepSeek	OpenAI

Charts

Partial coverage. Terminus-2 – DeepSeek V4 Flash (max): 219 of 221 GS-QA2 tasks; Codex – GPT-5.6 Luna (high): Earth-Bench V2 incomplete; GeoBenchX incomplete; 46 of 221 GS-QA2 tasks. Grey placeholders identify these entries in the index, cost and output token charts; their height does not represent a value. Comparable bars appear when first-attempt coverage is complete. Their available results remain in the side-by-side table.

Geospatial Agent Index

Equal-weight average of the evaluation scores, 0 to 100 · Higher is better

Data table: Geospatial Agent Index

Geospatial Agent Index
Model	Creator	Geospatial Agent Index	Range while attempts are pending	Benchmarks covered	Coverage (attempts)

Cost per task

Average cost per task (USD) · Lower is better

How to read this chart

Not shown: partial coverage. 2 entries without a first attempt on every index task. What is still running is on the models page.

Data table: Cost per task

Cost per task
Model	Creator	Cost per task	Coverage (attempts)

Output tokens per task

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

How to read this chart

Not shown: partial coverage. 2 entries without a first attempt on every index task. What is still running is on the models page.

Data table: Output tokens per task

Output tokens per task
Model	Creator	Output tokens per task	Coverage (attempts)

Frequently asked questions

Which scores higher on the Geospatial Agent Index, Terminus-2 – DeepSeek V4 Flash (max) or Codex – GPT-5.6 Luna (high)?

Not comparable yet: Terminus-2 – DeepSeek V4 Flash (max) has partial coverage (219 of 221 GS-QA2 tasks) and Codex – GPT-5.6 Luna (high) has partial coverage (Earth-Bench V2 incomplete; GeoBenchX incomplete; 46 of 221 GS-QA2 tasks), so it is not ranked. Terminus-2 – DeepSeek V4 Flash (max): 486 of 722 scheduled attempts. Codex – GPT-5.6 Luna (high): 46 of 572 scheduled attempts. Coverage is partial; scores can change as more attempts are decided.

Which is cheaper per task, Terminus-2 – DeepSeek V4 Flash (max) or Codex – GPT-5.6 Luna (high)?

Codex – GPT-5.6 Luna (high), at $0.0083 against $0.061 for Terminus-2 – DeepSeek V4 Flash (max).

Which writes fewer output tokens per task, Terminus-2 – DeepSeek V4 Flash (max) or Codex – GPT-5.6 Luna (high)?

Codex – GPT-5.6 Luna (high), at 2k against 29k for Terminus-2 – DeepSeek V4 Flash (max).

Which has the larger context window, Terminus-2 – DeepSeek V4 Flash (max) or Codex – GPT-5.6 Luna (high)?

Not known yet: Codex – GPT-5.6 Luna (high) has no context window data.

More: Terminus-2 – DeepSeek V4 Flash (max) · Codex – GPT-5.6 Luna (high) · all comparisons