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Anthropic: geospatial agent results

Helps you choose the best Anthropic model for geospatial work: GIS and Earth observation agent tasks, vision and knowledge, with cost and time.

Overview

  • For intelligence, the top Anthropic models are Claude Opus 5.5 (xhigh) (89), Claude Opus 5.5 (high) (87) and Claude Opus 5.5 (medium) (85) on the Geospatial Intelligence Index (Text only).
  • For cost, the cheapest per agent task are Claude Haiku 5.5 (low) ($0.0053), Claude Haiku 5.5 (medium) ($0.0063) and Claude Haiku 5.5 (high) ($0.0085).
  • For speed, the fastest per agent task are Claude Opus 5.5 (low) (0.4 min), Claude Sonnet 5.5 (medium) (0.4 min) and Claude Sonnet 5.5 (low) (0.4 min).
  • For context window, the largest are Claude Sonnet 4.6: 1M tokens, Claude Opus 5.5: 1M tokens and Claude Sonnet 5.5: 1M tokens.
  • Still being benchmarked (provisional): Claude Sonnet 4.6 (high).

Intelligence

Geospatial Intelligence Index, Text only · Higher is better

IntelligenceScores 0 to 100: Claude Opus 5.5 (xhigh): 89; Claude Opus 5.5 (high): 87; Claude Opus 5.5 (medium): 85; Claude Opus 5 (high): 84; Claude Sonnet 5.5 (xhigh): 84; Claude Sonnet 5.5 (high): 84; Claude Opus 4.8 (high): 83; Claude Haiku 5.5 (xhigh): 82; Claude Opus 5.5 (low): 82; Claude Haiku 5.5 (high): 81; Claude Sonnet 5 (high): 81; Claude Opus 4.7 (high): 81; Claude Haiku 5.5 (medium): 79; Claude Sonnet 5.5 (medium): 79; Claude Haiku 5.5 (low): 79; Claude Sonnet 5.5 (low): 78; Claude Haiku 4.5 (Reasoning): 660255075100Claude Opus 5.5 (xhigh)89Claude Opus 5.5 (high)87Claude Opus 5.5 (medium)85Claude Opus 5 (high)84Claude Sonnet 5.5 (xhigh)84Claude Sonnet 5.5 (high)84Claude Opus 4.8 (high)83Claude Haiku 5.5 (xhigh)82Claude Opus 5.5 (low)82Claude Haiku 5.5 (high)81Claude Sonnet 5 (high)81Claude Opus 4.7 (high)81Claude Haiku 5.5 (medium)79Claude Sonnet 5.5 (medium)79Claude Haiku 5.5 (low)79Claude Sonnet 5.5 (low)78Claude Haiku 4.5 (Reasoning)66
Data table: Intelligence

Cost per task

USD per agent task · Lower is better

Cost per taskCost per task in US dollars: Claude Haiku 5.5 (low), Claude Code: $0.0053; Claude Haiku 5.5 (medium), Claude Code: $0.0063; Claude Haiku 5.5 (high), Claude Code: $0.0085; Claude Haiku 5.5 (xhigh), Claude Code: $0.017; Claude Sonnet 5.5 (low), Claude Code: $0.043; Claude Sonnet 5.5 (medium), Claude Code: $0.046; Claude Sonnet 5.5 (high), Claude Code: $0.055; Claude Opus 5.5 (low), Claude Code: $0.081; Claude Haiku 4.5 (Reasoning), Claude Code: $0.092; Claude Sonnet 5.5 (xhigh), Claude Code: $0.11; Claude Opus 5.5 (medium), Claude Code: $0.11; Claude Opus 5.5 (high), Claude Code: $0.13; Claude Sonnet 5 (high), Claude Code: $0.20; Claude Opus 5.5 (xhigh), Claude Code: $0.25; Claude Opus 4.8 (high), Claude Code: $0.26; Claude Opus 5 (high), Claude Code: $0.32; Claude Opus 4.7 (high), Claude Code: $0.34$0$0.10$0.20$0.30$0.40Claude Haiku 5.5 (low)Claude Code$0.0053Claude Haiku 5.5 (medium)Claude Code$0.0063Claude Haiku 5.5 (high)Claude Code$0.0085Claude Haiku 5.5 (xhigh)Claude Code$0.017Claude Sonnet 5.5 (low)Claude Code$0.043Claude Sonnet 5.5 (medium)Claude Code$0.046Claude Sonnet 5.5 (high)Claude Code$0.055Claude Opus 5.5 (low)Claude Code$0.081Claude Haiku 4.5 (Reasoning)Claude Code$0.092Claude Sonnet 5.5 (xhigh)Claude Code$0.11Claude Opus 5.5 (medium)Claude Code$0.11Claude Opus 5.5 (high)Claude Code$0.13Claude Sonnet 5 (high)Claude Code$0.20Claude Opus 5.5 (xhigh)Claude Code$0.25Claude Opus 4.8 (high)Claude Code$0.26Claude Opus 5 (high)Claude Code$0.32Claude Opus 4.7 (high)Claude Code$0.34
Data table: Cost per task

Time per task

Minutes per agent task · Lower is better

Time per taskTime per task: Claude Opus 5.5 (low), Claude Code: 0.4 min; Claude Sonnet 5.5 (medium), Claude Code: 0.4 min; Claude Sonnet 5.5 (low), Claude Code: 0.4 min; Claude Opus 5.5 (medium), Claude Code: 0.5 min; Claude Sonnet 5.5 (high), Claude Code: 0.6 min; Claude Opus 5.5 (high), Claude Code: 0.7 min; Claude Opus 4.8 (high), Claude Code: 0.9 min; Claude Haiku 5.5 (low), Claude Code: 0.9 min; Claude Opus 4.7 (high), Claude Code: 0.9 min; Claude Haiku 5.5 (medium), Claude Code: 1.0 min; Claude Opus 5 (high), Claude Code: 1.1 min; Claude Sonnet 5.5 (xhigh), Claude Code: 1.2 min; Claude Haiku 5.5 (high), Claude Code: 1.4 min; Claude Opus 5.5 (xhigh), Claude Code: 1.4 min; Claude Sonnet 5 (high), Claude Code: 1.5 min; Claude Haiku 4.5 (Reasoning), Claude Code: 1.6 min; Claude Haiku 5.5 (xhigh), Claude Code: 2.5 min01234Claude Opus 5.5 (low)Claude Code0.4 minClaude Sonnet 5.5 (medium)Claude Code0.4 minClaude Sonnet 5.5 (low)Claude Code0.4 minClaude Opus 5.5 (medium)Claude Code0.5 minClaude Sonnet 5.5 (high)Claude Code0.6 minClaude Opus 5.5 (high)Claude Code0.7 minClaude Opus 4.8 (high)Claude Code0.9 minClaude Haiku 5.5 (low)Claude Code0.9 minClaude Opus 4.7 (high)Claude Code0.9 minClaude Haiku 5.5 (medium)Claude Code1.0 minClaude Opus 5 (high)Claude Code1.1 minClaude Sonnet 5.5 (xhigh)Claude Code1.2 minClaude Haiku 5.5 (high)Claude Code1.4 minClaude Opus 5.5 (xhigh)Claude Code1.4 minClaude Sonnet 5 (high)Claude Code1.5 minClaude Haiku 4.5 (Reasoning)Claude Code1.6 minClaude Haiku 5.5 (xhigh)Claude Code2.5 min
Data table: Time per task

Models

Claude Opus 5.5

Closed weightsReads images

1M token context · Released 22 September 2026

$4.00 input · $20.00 output per 1M tokens

Claude Opus 5

Closed weightsReads images

1M token context · Released 24 July 2026

$5.00 input · $25.00 output per 1M tokens

Claude Sonnet 5.5

Closed weightsReads images

1M token context · Released 28 September 2026

$2.00 input · $10.00 output per 1M tokens

Claude Opus 4.8

Closed weightsReads images

1M token context · Released 28 May 2026

$5.00 input · $25.00 output per 1M tokens

Claude Haiku 5.5

Closed weightsReads images

1M token context · Released 7 October 2026

$0.10 input · $0.50 output per 1M tokens

Claude Sonnet 5

Closed weightsReads images

1M token context · Released 30 June 2026

$2.00 input · $10.00 output per 1M tokens

Claude Opus 4.7

Closed weightsReads images

1M token context · Released 16 April 2026

$5.00 input · $25.00 output per 1M tokens

Claude Haiku 4.5

Closed weightsReads images

200K token context · Released 15 October 2025

$1.00 input · $5.00 output per 1M tokens

Claude Sonnet 4.6

Closed weightsReads images

1M token context · Released 17 February 2026

$3.00 input · $15.00 output per 1M tokens

Intelligence

Text only

Geospatial Intelligence Index: Text only

Weighted average of agent tasks, guided workflows and geospatial knowledge, 0 to 100 · Higher is better

Geospatial Intelligence Index: Text onlyScores 0 to 100: Claude Opus 5.5 (xhigh): 89; Claude Opus 5.5 (high): 87; GPT-6.1 Sol (medium): 86; Claude Opus 5.5 (medium): 85; Claude Opus 5 (high): 84; Claude Sonnet 5.5 (xhigh): 84; Claude Sonnet 5.5 (high): 84; Claude Opus 4.8 (high): 83; Claude Haiku 5.5 (xhigh): 82; Claude Opus 5.5 (low): 82; Claude Haiku 5.5 (high): 81; Claude Sonnet 5 (high): 81; Claude Opus 4.7 (high): 81; Claude Haiku 5.5 (medium): 79; DeepSeek V4 Pro (max): 79; Claude Sonnet 5.5 (medium): 79; Gemini 3.8 Flash (low): 79; Claude Haiku 5.5 (low): 79; Claude Sonnet 5.5 (low): 78; Claude Haiku 4.5 (Reasoning): 660255075100Claude Opus 5.5 (xhigh)89Claude Opus 5.5 (high)87GPT-6.1 Sol (medium)86Claude Opus 5.5 (medium)85Claude Opus 5 (high)84Claude Sonnet 5.5 (xhigh)84Claude Sonnet 5.5 (high)84Claude Opus 4.8 (high)83Claude Haiku 5.5 (xhigh)82Claude Opus 5.5 (low)82Claude Haiku 5.5 (high)81Claude Sonnet 5 (high)81Claude Opus 4.7 (high)81Claude Haiku 5.5 (medium)79DeepSeek V4 Pro (max)79Claude Sonnet 5.5 (medium)79Gemini 3.8 Flash (low)79Claude Haiku 5.5 (low)79Claude Sonnet 5.5 (low)78Claude Haiku 4.5 (Reasoning)66
How to read this chart

What this metric means. A weighted average of group scores, each 0 to 100: Agent tasks 4/6, Guided workflows 1/6, Geospatial knowledge 1/6.

Bars. Every Anthropic model with a result, highlighted, and the strongest models from other labs, faded, for context. Provisional: not yet ranked.

Data table: Geospatial Intelligence Index: Text only
Geospatial Intelligence Index: Text only
ModelDeveloperGeospatial Intelligence Index: Text only
Claude Opus 5.5 (xhigh)Anthropic89
Claude Opus 5.5 (high)Anthropic87
GPT-6.1 Sol (medium)OpenAI86
Claude Opus 5.5 (medium)Anthropic85
Claude Opus 5 (high)Anthropic84
Claude Sonnet 5.5 (xhigh)Anthropic84
Claude Sonnet 5.5 (high)Anthropic84
Claude Opus 4.8 (high)Anthropic83
Claude Haiku 5.5 (xhigh)Anthropic82
Claude Opus 5.5 (low)Anthropic82
Claude Haiku 5.5 (high)Anthropic81
Claude Sonnet 5 (high)Anthropic81
Claude Opus 4.7 (high)Anthropic81
Claude Haiku 5.5 (medium)Anthropic79
DeepSeek V4 Pro (max)DeepSeek79
Claude Sonnet 5.5 (medium)Anthropic79
Gemini 3.8 Flash (low)Google79
Claude Haiku 5.5 (low)Anthropic79
Claude Sonnet 5.5 (low)Anthropic78
Claude Haiku 4.5 (Reasoning)Anthropic66

Text + vision

Geospatial Intelligence Index: Text + vision

Weighted average of agent tasks, vision, guided workflows and geospatial knowledge, 0 to 100 · Higher is better

Geospatial Intelligence Index: Text + visionScores 0 to 100: Claude Opus 5.5 (xhigh): 83; Claude Opus 5.5 (high): 81; GPT-6.1 Sol (xhigh): 80; Claude Sonnet 5.5 (xhigh): 79; Claude Sonnet 5.5 (high): 78; Claude Opus 5 (high): 77; Claude Haiku 5.5 (xhigh): 75; Claude Opus 4.8 (high): 74; Claude Sonnet 5 (high): 73; Claude Opus 4.7 (high): 73; Claude Haiku 5.5 (high): 72; Claude Haiku 4.5 (Reasoning): 530255075100Claude Opus 5.5 (xhigh)83Claude Opus 5.5 (high)81GPT-6.1 Sol (xhigh)80Claude Sonnet 5.5 (xhigh)79Claude Sonnet 5.5 (high)78Claude Opus 5 (high)77Claude Haiku 5.5 (xhigh)75Claude Opus 4.8 (high)74Claude Sonnet 5 (high)73Claude Opus 4.7 (high)73Claude Haiku 5.5 (high)72Claude Haiku 4.5 (Reasoning)53
How to read this chart

What this metric means. A weighted average of group scores, each 0 to 100: Agent tasks 4/8, Vision 2/8, Guided workflows 1/8, Geospatial knowledge 1/8.

Bars. Every Anthropic model with a result, highlighted, and the strongest models from other labs, faded, for context. Provisional: not yet ranked.

Data table: Geospatial Intelligence Index: Text + vision
Geospatial Intelligence Index: Text + vision
ModelDeveloperGeospatial Intelligence Index: Text + vision
Claude Opus 5.5 (xhigh)Anthropic83
Claude Opus 5.5 (high)Anthropic81
GPT-6.1 Sol (xhigh)OpenAI80
Claude Sonnet 5.5 (xhigh)Anthropic79
Claude Sonnet 5.5 (high)Anthropic78
Claude Opus 5 (high)Anthropic77
Claude Haiku 5.5 (xhigh)Anthropic75
Claude Opus 4.8 (high)Anthropic74
Claude Sonnet 5 (high)Anthropic73
Claude Opus 4.7 (high)Anthropic73
Claude Haiku 5.5 (high)Anthropic72
Claude Haiku 4.5 (Reasoning)Anthropic53

Provisional, so not on these charts: Claude Sonnet 4.6 (high). Their finished evaluations are in the charts below.

Agent tasks

Text only

Geospatial Agent Index: Text only

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

Geospatial Agent Index: Text onlyScores 0 to 100: Claude Opus 5.5 (xhigh), Claude Code: 85; Claude Opus 5.5 (high), Claude Code: 82; GPT-6.1 Sol (xhigh), Codex: 82; Claude Opus 5.5 (medium), Claude Code: 80; Claude Opus 5 (high), Claude Code: 80; Claude Sonnet 5.5 (xhigh), Claude Code: 79; Claude Sonnet 5.5 (high), Claude Code: 78; Claude Opus 4.8 (high), Claude Code: 76; Claude Haiku 5.5 (xhigh), Claude Code: 76; Claude Haiku 5.5 (high), Claude Code: 76; Claude Sonnet 5 (high), Claude Code: 74; Claude Opus 5.5 (low), Claude Code: 74; Claude Opus 4.7 (high), Claude Code: 74; GLM-5.3 (max), Claude Code: 73; Claude Haiku 5.5 (medium), Claude Code: 72; Kimi K3 (Reasoning), Terminus-2: 72; Claude Sonnet 5.5 (medium), Claude Code: 71; Claude Haiku 5.5 (low), Claude Code: 70; Claude Sonnet 5.5 (low), Claude Code: 69; Claude Haiku 4.5 (Reasoning), Claude Code: 580255075100Claude Opus 5.5 (xhigh)Claude Code85Claude Opus 5.5 (high)Claude Code82GPT-6.1 Sol (xhigh)Codex82Claude Opus 5.5 (medium)Claude Code80Claude Opus 5 (high)Claude Code80Claude Sonnet 5.5 (xhigh)Claude Code79Claude Sonnet 5.5 (high)Claude Code78Claude Opus 4.8 (high)Claude Code76Claude Haiku 5.5 (xhigh)Claude Code76Claude Haiku 5.5 (high)Claude Code76Claude Sonnet 5 (high)Claude Code74Claude Opus 5.5 (low)Claude Code74Claude Opus 4.7 (high)Claude Code74GLM-5.3 (max)Claude Code73Claude Haiku 5.5 (medium)Claude Code72Kimi K3 (Reasoning)Terminus-272Claude Sonnet 5.5 (medium)Claude Code71Claude Haiku 5.5 (low)Claude Code70Claude Sonnet 5.5 (low)Claude Code69Claude Haiku 4.5 (Reasoning)Claude Code58
How to read this chart

Bars. Every Anthropic model with a result, highlighted, and the strongest models from other labs, faded, for context. Provisional: not yet ranked.

Data table: Geospatial Agent Index: Text only

Text + vision

Geospatial Agent Index: Text + vision

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

Geospatial Agent Index: Text + visionScores 0 to 100: Claude Opus 5.5 (xhigh), Claude Code: 88; Claude Opus 5.5 (high), Claude Code: 84; GPT-6.1 Sol (xhigh), Codex: 84; Claude Sonnet 5.5 (xhigh), Claude Code: 82; Claude Opus 5 (high), Claude Code: 81; Claude Sonnet 5.5 (high), Claude Code: 78; Claude Opus 5.5 (low), Claude Code: 78; Claude Haiku 5.5 (xhigh), Claude Code: 77; Claude Sonnet 5 (high), Claude Code: 76; Claude Opus 4.8 (high), Claude Code: 75; Claude Haiku 5.5 (high), Claude Code: 74; Claude Opus 4.7 (high), Claude Code: 74; GLM-5.3-Flash (max), Claude Code: 73; DeepSeek V4.1 Flash (max), Codex: 73; Claude Haiku 5.5 (low), Claude Code: 72; Claude Sonnet 5.5 (low), Claude Code: 71; Claude Haiku 4.5 (Reasoning), Claude Code: 480255075100Claude Opus 5.5 (xhigh)Claude Code88Claude Opus 5.5 (high)Claude Code84GPT-6.1 Sol (xhigh)Codex84Claude Sonnet 5.5 (xhigh)Claude Code82Claude Opus 5 (high)Claude Code81Claude Sonnet 5.5 (high)Claude Code78Claude Opus 5.5 (low)Claude Code78Claude Haiku 5.5 (xhigh)Claude Code77Claude Sonnet 5 (high)Claude Code76Claude Opus 4.8 (high)Claude Code75Claude Haiku 5.5 (high)Claude Code74Claude Opus 4.7 (high)Claude Code74GLM-5.3-Flash (max)Claude Code73DeepSeek V4.1 Flash (max)Codex73Claude Haiku 5.5 (low)Claude Code72Claude Sonnet 5.5 (low)Claude Code71Claude Haiku 4.5 (Reasoning)Claude Code48
How to read this chart

Bars. Every Anthropic model with a result, highlighted, and the strongest models from other labs, faded, for context. Provisional: not yet ranked.

Data table: Geospatial Agent Index: Text + vision

Provisional, so not on the index charts: Claude Sonnet 4.6 (high), Terminus-2. Their finished evaluations are in the charts below.

Earth-Bench V2

Earth observation data analysis · 0 to 100 · Higher is better

  • Striped: provisional, not yet ranked
Earth-Bench V2Scores 0 to 100: Claude Opus 5.5 (high), Claude Code: 79; Claude Opus 5.5 (xhigh), Claude Code: 77; GPT-6 Sol (high), Codex: 75; GLM-5.3 (max), Claude Code: 74; Claude Opus 5 (high), Claude Code: 74; Claude Opus 5.5 (medium), Claude Code: 72; Claude Haiku 5.5 (high), Claude Code: 72; Claude Sonnet 5.5 (high), Claude Code: 71; Claude Opus 4.8 (high), Claude Code: 71; Claude Opus 4.7 (high), Claude Code: 69; Claude Sonnet 5.5 (xhigh), Claude Code: 68; Claude Haiku 5.5 (xhigh), Claude Code: 68; Claude Sonnet 5 (high), Claude Code: 68; Claude Haiku 5.5 (medium), Claude Code: 68; Claude Haiku 5.5 (low), Claude Code: 62; Claude Opus 5.5 (low), Claude Code: 59; Claude Sonnet 5.5 (medium), Claude Code: 58; Claude Sonnet 5.5 (low), Claude Code: 56; Claude Haiku 4.5 (Reasoning), Claude Code: 51; Claude Sonnet 4.6 (high), Terminus-2: 59 (provisional, not yet ranked)0255075100Claude Opus 5.5 (high)Claude Code79Claude Opus 5.5 (xhigh)Claude Code77GPT-6 Sol (high)Codex75GLM-5.3 (max)Claude Code74Claude Opus 5 (high)Claude Code74Claude Opus 5.5 (medium)Claude Code72Claude Haiku 5.5 (high)Claude Code72Claude Sonnet 5.5 (high)Claude Code71Claude Opus 4.8 (high)Claude Code71Claude Opus 4.7 (high)Claude Code69Claude Sonnet 5.5 (xhigh)Claude Code68Claude Haiku 5.5 (xhigh)Claude Code68Claude Sonnet 5 (high)Claude Code68Claude Haiku 5.5 (medium)Claude Code68Claude Haiku 5.5 (low)Claude Code62Claude Opus 5.5 (low)Claude Code59Claude Sonnet 5.5 (medium)Claude Code58Claude Sonnet 5.5 (low)Claude Code56Claude Haiku 4.5 (Reasoning)Claude Code51Claude Sonnet 4.6 (high)Terminus-2 · provisional59
Data table: Earth-Bench V2

GeoBenchX

Maps, numbers and lists from country and city data; some tasks should be declined · 0 to 100 · Higher is better

GeoBenchXScores 0 to 100: Claude Opus 5.5 (xhigh), Claude Code: 83; Claude Sonnet 5.5 (high), Claude Code: 81; Claude Sonnet 5.5 (xhigh), Claude Code: 81; Claude Opus 5.5 (medium), Claude Code: 79; GPT-6.1 Sol (medium), Codex: 79; Claude Opus 5.5 (high), Claude Code: 79; Claude Haiku 5.5 (xhigh), Claude Code: 77; Claude Sonnet 5 (high), Claude Code: 77; Claude Opus 5.5 (low), Claude Code: 77; Claude Sonnet 5.5 (low), Claude Code: 77; Claude Sonnet 5.5 (medium), Claude Code: 76; Claude Opus 5 (high), Claude Code: 75; Gemini 3.8 Flash (low), Terminus-2: 74; Claude Opus 4.8 (high), Claude Code: 73; Claude Haiku 5.5 (low), Claude Code: 73; Claude Opus 4.7 (high), Claude Code: 73; Claude Haiku 5.5 (high), Claude Code: 72; Claude Haiku 5.5 (medium), Claude Code: 71; Claude Sonnet 4.6 (high), Terminus-2: 57; Claude Haiku 4.5 (Reasoning), Claude Code: 530255075100Claude Opus 5.5 (xhigh)Claude Code83Claude Sonnet 5.5 (high)Claude Code81Claude Sonnet 5.5 (xhigh)Claude Code81Claude Opus 5.5 (medium)Claude Code79GPT-6.1 Sol (medium)Codex79Claude Opus 5.5 (high)Claude Code79Claude Haiku 5.5 (xhigh)Claude Code77Claude Sonnet 5 (high)Claude Code77Claude Opus 5.5 (low)Claude Code77Claude Sonnet 5.5 (low)Claude Code77Claude Sonnet 5.5 (medium)Claude Code76Claude Opus 5 (high)Claude Code75Gemini 3.8 Flash (low)Terminus-274Claude Opus 4.8 (high)Claude Code73Claude Haiku 5.5 (low)Claude Code73Claude Opus 4.7 (high)Claude Code73Claude Haiku 5.5 (high)Claude Code72Claude Haiku 5.5 (medium)Claude Code71Claude Sonnet 4.6 (high)Terminus-2 · provisional57Claude Haiku 4.5 (Reasoning)Claude Code53
Data table: GeoBenchX

GS-QA2

Spatial data reasoning over map and elevation data · 0 to 100 · Higher is better

GS-QA2Scores 0 to 100: Claude Opus 5.5 (xhigh), Claude Code: 94; GPT-6.1 Sol (xhigh), Codex: 94; Claude Opus 5 (high), Claude Code: 91; Claude Opus 5.5 (medium), Claude Code: 90; Claude Opus 5.5 (high), Claude Code: 90; DeepSeek V4.1 Flash (max), Codex: 89; Claude Sonnet 5.5 (xhigh), Claude Code: 87; Claude Opus 5.5 (low), Claude Code: 86; Claude Opus 4.8 (high), Claude Code: 84; Claude Haiku 5.5 (high), Claude Code: 83; Claude Sonnet 5.5 (high), Claude Code: 83; Claude Haiku 5.5 (xhigh), Claude Code: 81; Claude Haiku 5.5 (medium), Claude Code: 79; Claude Opus 4.7 (high), Claude Code: 79; Claude Sonnet 5.5 (medium), Claude Code: 79; Claude Sonnet 5 (high), Claude Code: 77; Claude Sonnet 5.5 (low), Claude Code: 76; Claude Haiku 5.5 (low), Claude Code: 75; Claude Haiku 4.5 (Reasoning), Claude Code: 690255075100Claude Opus 5.5 (xhigh)Claude Code94GPT-6.1 Sol (xhigh)Codex94Claude Opus 5 (high)Claude Code91Claude Opus 5.5 (medium)Claude Code90Claude Opus 5.5 (high)Claude Code90DeepSeek V4.1 Flash (max)Codex89Claude Sonnet 5.5 (xhigh)Claude Code87Claude Opus 5.5 (low)Claude Code86Claude Opus 4.8 (high)Claude Code84Claude Haiku 5.5 (high)Claude Code83Claude Sonnet 5.5 (high)Claude Code83Claude Haiku 5.5 (xhigh)Claude Code81Claude Haiku 5.5 (medium)Claude Code79Claude Opus 4.7 (high)Claude Code79Claude Sonnet 5.5 (medium)Claude Code79Claude Sonnet 5 (high)Claude Code77Claude Sonnet 5.5 (low)Claude Code76Claude Haiku 5.5 (low)Claude Code75Claude Haiku 4.5 (Reasoning)Claude Code69
Data table: GS-QA2

GeoAgentBench

Guided workflows: multi-step spatial execution · 0 to 100 · Higher is better

GeoAgentBenchScores 0 to 100: Claude Opus 5.5 (high), Claude Code: 100; Claude Haiku 5.5 (xhigh), Claude Code: 100; Claude Opus 5 (high), Claude Code: 100; GPT-6.1 Sol (medium), Codex: 100; Claude Opus 5.5 (medium), Claude Code: 98; Claude Sonnet 5.5 (medium), Claude Code: 98; Claude Sonnet 5.5 (high), Claude Code: 98; Claude Haiku 5.5 (high), Claude Code: 98; Claude Opus 5.5 (xhigh), Claude Code: 98; Claude Sonnet 5.5 (xhigh), Claude Code: 98; Claude Sonnet 5 (high), Claude Code: 98; Gemini 3.8 Flash (low), Terminus-2: 98; Claude Sonnet 4.6 (high), Terminus-2: 96; Claude Opus 5.5 (low), Claude Code: 96; Claude Opus 4.8 (high), Claude Code: 96; Claude Opus 4.7 (high), Claude Code: 96; Claude Haiku 5.5 (medium), Claude Code: 94; Claude Sonnet 5.5 (low), Claude Code: 94; Claude Haiku 5.5 (low), Claude Code: 92; Claude Haiku 4.5 (Reasoning), Claude Code: 780255075100Claude Opus 5.5 (high)Claude Code100Claude Haiku 5.5 (xhigh)Claude Code100Claude Opus 5 (high)Claude Code100GPT-6.1 Sol (medium)Codex100Claude Opus 5.5 (medium)Claude Code98Claude Sonnet 5.5 (medium)Claude Code98Claude Sonnet 5.5 (high)Claude Code98Claude Haiku 5.5 (high)Claude Code98Claude Opus 5.5 (xhigh)Claude Code98Claude Sonnet 5.5 (xhigh)Claude Code98Claude Sonnet 5 (high)Claude Code98Gemini 3.8 Flash (low)Terminus-298Claude Sonnet 4.6 (high)Terminus-2 · provisional96Claude Opus 5.5 (low)Claude Code96Claude Opus 4.8 (high)Claude Code96Claude Opus 4.7 (high)Claude Code96Claude Haiku 5.5 (medium)Claude Code94Claude Sonnet 5.5 (low)Claude Code94Claude Haiku 5.5 (low)Claude Code92Claude Haiku 4.5 (Reasoning)Claude Code78
Data table: GeoAgentBench

GeoAnalystBench

Guided workflows: spatial workflow and code generation · 0 to 100 · Higher is better

GeoAnalystBenchScores 0 to 100: Claude Sonnet 4.6 (high), Terminus-2: 100; Claude Opus 5.5 (high), Claude Code: 100; Claude Sonnet 5.5 (high), Claude Code: 100; Claude Opus 5.5 (xhigh), Claude Code: 100; Claude Opus 5.5 (low), Claude Code: 100; Claude Haiku 5.5 (low), Claude Code: 100; Claude Opus 4.8 (high), Claude Code: 100; Claude Opus 4.7 (high), Claude Code: 100; DeepSeek V4 Pro (max), Terminus-2: 100; GLM-5.2 (high), Terminus-2: 100; Claude Opus 5.5 (medium), Claude Code: 95; Claude Sonnet 5.5 (medium), Claude Code: 95; Claude Haiku 5.5 (medium), Claude Code: 95; Claude Sonnet 5.5 (xhigh), Claude Code: 95; Claude Haiku 5.5 (xhigh), Claude Code: 95; Claude Sonnet 5.5 (low), Claude Code: 95; Claude Sonnet 5 (high), Claude Code: 95; Claude Opus 5 (high), Claude Code: 89; Claude Haiku 5.5 (high), Claude Code: 84; Claude Haiku 4.5 (Reasoning), Claude Code: 740255075100Claude Sonnet 4.6 (high)Terminus-2 · provisional100Claude Opus 5.5 (high)Claude Code100Claude Sonnet 5.5 (high)Claude Code100Claude Opus 5.5 (xhigh)Claude Code100Claude Opus 5.5 (low)Claude Code100Claude Haiku 5.5 (low)Claude Code100Claude Opus 4.8 (high)Claude Code100Claude Opus 4.7 (high)Claude Code100DeepSeek V4 Pro (max)Terminus-2100GLM-5.2 (high)Terminus-2100Claude Opus 5.5 (medium)Claude Code95Claude Sonnet 5.5 (medium)Claude Code95Claude Haiku 5.5 (medium)Claude Code95Claude Sonnet 5.5 (xhigh)Claude Code95Claude Haiku 5.5 (xhigh)Claude Code95Claude Sonnet 5.5 (low)Claude Code95Claude Sonnet 5 (high)Claude Code95Claude Opus 5 (high)Claude Code89Claude Haiku 5.5 (high)Claude Code84Claude Haiku 4.5 (Reasoning)Claude Code74
Data table: GeoAnalystBench

OGD4All

Not in an index: questions on a city's open government data · 0 to 100 · Higher is better

OGD4AllScores 0 to 100: Claude Opus 4.8 (high), Claude Code: 97; Claude Opus 5.5 (medium), Claude Code: 97; Claude Sonnet 5.5 (xhigh), Claude Code: 97; Claude Haiku 5.5 (xhigh), Claude Code: 97; Claude Haiku 5.5 (high), Claude Code: 96; Claude Sonnet 5.5 (medium), Claude Code: 96; Claude Sonnet 5.5 (high), Claude Code: 96; Claude Opus 5.5 (xhigh), Claude Code: 96; Claude Sonnet 5.5 (low), Claude Code: 96; GLM-5.3 (max), Claude Code: 96; Claude Opus 5.5 (high), Claude Code: 95; Claude Haiku 5.5 (medium), Claude Code: 95; Claude Opus 5.5 (low), Claude Code: 95; Claude Opus 5 (high), Claude Code: 95; Claude Sonnet 5 (high), Claude Code: 95; Qwen 3.8 27B (xhigh), Qwen Code: 95; Claude Haiku 4.5 (Reasoning), Claude Code: 95; Claude Haiku 5.5 (low), Claude Code: 95; Claude Opus 4.7 (high), Claude Code: 950255075100Claude Opus 4.8 (high)Claude Code97Claude Opus 5.5 (medium)Claude Code97Claude Sonnet 5.5 (xhigh)Claude Code97Claude Haiku 5.5 (xhigh)Claude Code97Claude Haiku 5.5 (high)Claude Code96Claude Sonnet 5.5 (medium)Claude Code96Claude Sonnet 5.5 (high)Claude Code96Claude Opus 5.5 (xhigh)Claude Code96Claude Sonnet 5.5 (low)Claude Code96GLM-5.3 (max)Claude Code96Claude Opus 5.5 (high)Claude Code95Claude Haiku 5.5 (medium)Claude Code95Claude Opus 5.5 (low)Claude Code95Claude Opus 5 (high)Claude Code95Claude Sonnet 5 (high)Claude Code95Qwen 3.8 27B (xhigh)Qwen Code95Claude Haiku 4.5 (Reasoning)Claude Code95Claude Haiku 5.5 (low)Claude Code95Claude Opus 4.7 (high)Claude Code95
Data table: OGD4All

GeoNatureAgent

Not in an index: environmental raster analysis over named regions · 0 to 100 · Higher is better

GeoNatureAgentScores 0 to 100: Claude Opus 5.5 (medium), Claude Code: 100; Claude Opus 5.5 (high), Claude Code: 100; Claude Sonnet 5.5 (medium), Claude Code: 100; Claude Sonnet 5.5 (high), Claude Code: 100; Claude Haiku 5.5 (medium), Claude Code: 100; Claude Haiku 5.5 (high), Claude Code: 100; Claude Opus 5.5 (xhigh), Claude Code: 100; Claude Sonnet 5.5 (xhigh), Claude Code: 100; Claude Haiku 5.5 (xhigh), Claude Code: 100; Claude Opus 5.5 (low), Claude Code: 100; Claude Sonnet 5.5 (low), Claude Code: 100; Claude Haiku 5.5 (low), Claude Code: 100; Claude Opus 5 (high), Claude Code: 100; Claude Sonnet 5 (high), Claude Code: 100; Claude Opus 4.8 (high), Claude Code: 100; Claude Opus 4.7 (high), Claude Code: 100; Qwen 3.8 27B (xhigh), Terminus-2: 100; Step 5 Preview (Reasoning), Terminus-2: 100; Claude Haiku 4.5 (Reasoning), Claude Code: 930255075100Claude Opus 5.5 (medium)Claude Code100Claude Opus 5.5 (high)Claude Code100Claude Sonnet 5.5 (medium)Claude Code100Claude Sonnet 5.5 (high)Claude Code100Claude Haiku 5.5 (medium)Claude Code100Claude Haiku 5.5 (high)Claude Code100Claude Opus 5.5 (xhigh)Claude Code100Claude Sonnet 5.5 (xhigh)Claude Code100Claude Haiku 5.5 (xhigh)Claude Code100Claude Opus 5.5 (low)Claude Code100Claude Sonnet 5.5 (low)Claude Code100Claude Haiku 5.5 (low)Claude Code100Claude Opus 5 (high)Claude Code100Claude Sonnet 5 (high)Claude Code100Claude Opus 4.8 (high)Claude Code100Claude Opus 4.7 (high)Claude Code100Qwen 3.8 27B (xhigh)Terminus-2100Step 5 Preview (Reasoning)Terminus-2100Claude Haiku 4.5 (Reasoning)Claude Code93
Data table: GeoNatureAgent

MultiGlobeQA

Not in an index: spatial reasoning over facts about places worldwide · 0 to 100 · Higher is better

MultiGlobeQAScores 0 to 100: Step 5 Preview (Reasoning), Terminus-2: 83; Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: 82; Claude Sonnet 5.5 (xhigh), Claude Code: 79; Claude Opus 5.5 (xhigh), Claude Code: 79; Claude Opus 5 (high), Claude Code: 79; Claude Opus 5.5 (medium), Claude Code: 78; Claude Opus 5.5 (high), Claude Code: 78; Claude Opus 5.5 (low), Claude Code: 78; Claude Opus 4.7 (high), Claude Code: 77; Claude Sonnet 5.5 (high), Claude Code: 77; Claude Opus 4.8 (high), Claude Code: 75; Claude Haiku 5.5 (xhigh), Claude Code: 75; Claude Sonnet 5.5 (low), Claude Code: 75; Claude Haiku 5.5 (high), Claude Code: 74; Claude Sonnet 5.5 (medium), Claude Code: 74; Claude Sonnet 5 (high), Claude Code: 73; Claude Haiku 5.5 (medium), Claude Code: 73; Claude Haiku 5.5 (low), Claude Code: 72; Claude Haiku 4.5 (Reasoning), Claude Code: 700255075100Step 5 Preview (Reasoning)Terminus-283Nemotron 3.5 Super VL 120B (Reasoning)Terminus-282Claude Sonnet 5.5 (xhigh)Claude Code79Claude Opus 5.5 (xhigh)Claude Code79Claude Opus 5 (high)Claude Code79Claude Opus 5.5 (medium)Claude Code78Claude Opus 5.5 (high)Claude Code78Claude Opus 5.5 (low)Claude Code78Claude Opus 4.7 (high)Claude Code77Claude Sonnet 5.5 (high)Claude Code77Claude Opus 4.8 (high)Claude Code75Claude Haiku 5.5 (xhigh)Claude Code75Claude Sonnet 5.5 (low)Claude Code75Claude Haiku 5.5 (high)Claude Code74Claude Sonnet 5.5 (medium)Claude Code74Claude Sonnet 5 (high)Claude Code73Claude Haiku 5.5 (medium)Claude Code73Claude Haiku 5.5 (low)Claude Code72Claude Haiku 4.5 (Reasoning)Claude Code70
Data table: MultiGlobeQA

GeoAgentEval

Not in an index: building, auditing and repairing a PostGIS database · 0 to 100 · Higher is better

GeoAgentEvalScores 0 to 100: Claude Opus 5.5 (medium), Claude Code: 100; Claude Opus 5.5 (high), Claude Code: 100; Claude Sonnet 5.5 (high), Claude Code: 100; Claude Opus 5.5 (xhigh), Claude Code: 100; Claude Sonnet 5.5 (xhigh), Claude Code: 100; Claude Opus 5.5 (low), Claude Code: 100; Claude Sonnet 5.5 (low), Claude Code: 100; Claude Sonnet 5.5 (medium), Claude Code: 96; Claude Opus 5 (high), Claude Code: 96; GLM-5.3-Flash (max), Claude Code: 96; Step 5 Preview (Reasoning), Terminus-2: 95; Claude Haiku 5.5 (medium), Claude Code: 92; Claude Haiku 5.5 (high), Claude Code: 92; Claude Haiku 5.5 (xhigh), Claude Code: 92; Claude Haiku 5.5 (low), Claude Code: 92; Claude Sonnet 5 (high), Claude Code: 92; Claude Opus 4.8 (high), Claude Code: 92; Claude Opus 4.7 (high), Claude Code: 92; Claude Haiku 4.5 (Reasoning), Claude Code: 880255075100Claude Opus 5.5 (medium)Claude Code100Claude Opus 5.5 (high)Claude Code100Claude Sonnet 5.5 (high)Claude Code100Claude Opus 5.5 (xhigh)Claude Code100Claude Sonnet 5.5 (xhigh)Claude Code100Claude Opus 5.5 (low)Claude Code100Claude Sonnet 5.5 (low)Claude Code100Claude Sonnet 5.5 (medium)Claude Code96Claude Opus 5 (high)Claude Code96GLM-5.3-Flash (max)Claude Code96Step 5 Preview (Reasoning)Terminus-295Claude Haiku 5.5 (medium)Claude Code92Claude Haiku 5.5 (high)Claude Code92Claude Haiku 5.5 (xhigh)Claude Code92Claude Haiku 5.5 (low)Claude Code92Claude Sonnet 5 (high)Claude Code92Claude Opus 4.8 (high)Claude Code92Claude Opus 4.7 (high)Claude Code92Claude Haiku 4.5 (Reasoning)Claude Code88
Data table: GeoAgentEval

Vision

ThinkGeo

Vision agents: agents that look at images and use code · 0 to 100 · Higher is better

ThinkGeoScores 0 to 100: Claude Opus 5.5 (xhigh), Claude Code: 96; Claude Sonnet 5.5 (xhigh), Claude Code: 89; GPT-6.1 Sol (xhigh), Codex: 88; Claude Opus 5.5 (medium), Claude Code: 87; Claude Opus 5.5 (high), Claude Code: 87; Claude Opus 5.5 (low), Claude Code: 85; Claude Opus 5 (high), Claude Code: 81; Claude Sonnet 5 (high), Claude Code: 81; Claude Sonnet 5.5 (medium), Claude Code: 77; Claude Sonnet 5.5 (high), Claude Code: 74; Claude Haiku 5.5 (xhigh), Claude Code: 74; GLM-5.3-Flash (max), Claude Code: 74; Claude Opus 4.7 (high), Claude Code: 72; Claude Haiku 5.5 (medium), Claude Code: 70; Claude Sonnet 5.5 (low), Claude Code: 70; Claude Haiku 5.5 (low), Claude Code: 70; Claude Opus 4.8 (high), Claude Code: 68; Claude Haiku 5.5 (high), Claude Code: 62; Claude Haiku 4.5 (Reasoning), Claude Code: 170255075100Claude Opus 5.5 (xhigh)Claude Code96Claude Sonnet 5.5 (xhigh)Claude Code89GPT-6.1 Sol (xhigh)Codex88Claude Opus 5.5 (medium)Claude Code87Claude Opus 5.5 (high)Claude Code87Claude Opus 5.5 (low)Claude Code85Claude Opus 5 (high)Claude Code81Claude Sonnet 5 (high)Claude Code81Claude Sonnet 5.5 (medium)Claude Code77Claude Sonnet 5.5 (high)Claude Code74Claude Haiku 5.5 (xhigh)Claude Code74GLM-5.3-Flash (max)Claude Code74Claude Opus 4.7 (high)Claude Code72Claude Haiku 5.5 (medium)Claude Code70Claude Sonnet 5.5 (low)Claude Code70Claude Haiku 5.5 (low)Claude Code70Claude Opus 4.8 (high)Claude Code68Claude Haiku 5.5 (high)Claude Code62Claude Haiku 4.5 (Reasoning)Claude Code17
Data table: ThinkGeo

OpenEarthAgent

Vision agents: agents that look at images and use code · 0 to 100 · Higher is better

OpenEarthAgentScores 0 to 100: Claude Opus 5.5 (medium), Claude Code: 100; Claude Sonnet 5.5 (medium), Claude Code: 100; Claude Opus 5.5 (xhigh), Claude Code: 100; Claude Opus 5.5 (low), Claude Code: 100; Claude Sonnet 5.5 (low), Claude Code: 100; Claude Opus 5 (high), Claude Code: 100; GPT-6.1 Sol (medium), Codex: 100; Claude Opus 5.5 (high), Claude Code: 94; Claude Haiku 5.5 (medium), Claude Code: 94; Claude Haiku 5.5 (high), Claude Code: 94; Claude Haiku 5.5 (xhigh), Claude Code: 94; Claude Haiku 5.5 (low), Claude Code: 94; DeepSeek V4.1 Flash (max), Codex: 94; Claude Sonnet 5.5 (high), Claude Code: 88; Claude Sonnet 5.5 (xhigh), Claude Code: 88; Claude Opus 4.8 (high), Claude Code: 88; Claude Opus 4.7 (high), Claude Code: 88; Claude Sonnet 5 (high), Claude Code: 82; Claude Haiku 4.5 (Reasoning), Claude Code: 240255075100Claude Opus 5.5 (medium)Claude Code100Claude Sonnet 5.5 (medium)Claude Code100Claude Opus 5.5 (xhigh)Claude Code100Claude Opus 5.5 (low)Claude Code100Claude Sonnet 5.5 (low)Claude Code100Claude Opus 5 (high)Claude Code100GPT-6.1 Sol (medium)Codex100Claude Opus 5.5 (high)Claude Code94Claude Haiku 5.5 (medium)Claude Code94Claude Haiku 5.5 (high)Claude Code94Claude Haiku 5.5 (xhigh)Claude Code94Claude Haiku 5.5 (low)Claude Code94DeepSeek V4.1 Flash (max)Codex94Claude Sonnet 5.5 (high)Claude Code88Claude Sonnet 5.5 (xhigh)Claude Code88Claude Opus 4.8 (high)Claude Code88Claude Opus 4.7 (high)Claude Code88Claude Sonnet 5 (high)Claude Code82Claude Haiku 4.5 (Reasoning)Claude Code24
Data table: OpenEarthAgent

Earth-Bench V2 images

Questions on images, no tools · 0 to 100 · Higher is better

Earth-Bench V2 imagesScores 0 to 100: GPT-5.6 Sol (high): 76; Claude Opus 5.5 (high): 74; Claude Opus 5.5 (xhigh): 70; Claude Haiku 5.5 (xhigh): 70; Claude Opus 5.5 (medium): 70; Qwen 3.8 27B (xhigh): 69; Claude Sonnet 5.5 (xhigh): 68; Claude Sonnet 5.5 (high): 68; Claude Opus 5 (high): 68; Claude Opus 4.7 (high): 68; Claude Sonnet 5.5 (medium): 68; Claude Opus 4.8 (high): 66; Claude Sonnet 5 (high): 66; Claude Haiku 5.5 (high): 60; Claude Haiku 5.5 (medium): 56; Claude Haiku 4.5 (Reasoning): 500255075100GPT-5.6 Sol (high)76Claude Opus 5.5 (high)74Claude Opus 5.5 (xhigh)70Claude Haiku 5.5 (xhigh)70Claude Opus 5.5 (medium)70Qwen 3.8 27B (xhigh)69Claude Sonnet 5.5 (xhigh)68Claude Sonnet 5.5 (high)68Claude Opus 5 (high)68Claude Opus 4.7 (high)68Claude Sonnet 5.5 (medium)68Claude Opus 4.8 (high)66Claude Sonnet 5 (high)66Claude Haiku 5.5 (high)60Claude Haiku 5.5 (medium)56Claude Haiku 4.5 (Reasoning)50
Data table: Earth-Bench V2 images

ThinkGeo images

Questions on images, no tools · 0 to 100 · Higher is better

ThinkGeo imagesScores 0 to 100: Claude Sonnet 5.5 (high): 50; Claude Opus 5.5 (xhigh): 48; Claude Sonnet 5.5 (xhigh): 47; Claude Opus 5.5 (high): 44; Claude Opus 5.5 (medium): 44; Claude Sonnet 5.5 (medium): 43; GPT-6 Luna (high): 43; Claude Opus 5 (high): 38; Qwen 3.8 27B (xhigh): 37; Claude Haiku 5.5 (xhigh): 35; Claude Haiku 5.5 (high): 35; Claude Haiku 5.5 (medium): 35; Claude Opus 4.8 (high): 34; Claude Sonnet 5 (high): 28; Claude Opus 4.7 (high): 27; Claude Haiku 4.5 (Reasoning): 190255075100Claude Sonnet 5.5 (high)50Claude Opus 5.5 (xhigh)48Claude Sonnet 5.5 (xhigh)47Claude Opus 5.5 (high)44Claude Opus 5.5 (medium)44Claude Sonnet 5.5 (medium)43GPT-6 Luna (high)43Claude Opus 5 (high)38Qwen 3.8 27B (xhigh)37Claude Haiku 5.5 (xhigh)35Claude Haiku 5.5 (high)35Claude Haiku 5.5 (medium)35Claude Opus 4.8 (high)34Claude Sonnet 5 (high)28Claude Opus 4.7 (high)27Claude Haiku 4.5 (Reasoning)19
Data table: ThinkGeo images

GeoChrono

Not in an index: change over time in aerial image series · 0 to 100 · Higher is better

GeoChronoScores 0 to 100: Claude Sonnet 5.5 (xhigh): 76; Claude Opus 5.5 (xhigh): 74; Claude Sonnet 5.5 (high): 74; Claude Opus 5.5 (high): 73; Claude Opus 5 (high): 71; Claude Haiku 5.5 (high): 68; Claude Opus 4.8 (high): 59; Claude Sonnet 5 (high): 55; Claude Opus 4.7 (high): 54; Claude Haiku 4.5 (Reasoning): 360255075100Claude Sonnet 5.5 (xhigh)76Claude Opus 5.5 (xhigh)74Claude Sonnet 5.5 (high)74Claude Opus 5.5 (high)73Claude Opus 5 (high)71Claude Haiku 5.5 (high)68Claude Opus 4.8 (high)59Claude Sonnet 5 (high)55Claude Opus 4.7 (high)54Claude Haiku 4.5 (Reasoning)36
Data table: GeoChrono
GeoChrono
ModelDeveloperGeoChrono
Claude Sonnet 5.5 (xhigh)Anthropic76
Claude Opus 5.5 (xhigh)Anthropic74
Claude Sonnet 5.5 (high)Anthropic74
Claude Opus 5.5 (high)Anthropic73
Claude Opus 5 (high)Anthropic71
Claude Haiku 5.5 (high)Anthropic68
Claude Opus 4.8 (high)Anthropic59
Claude Sonnet 5 (high)Anthropic55
Claude Opus 4.7 (high)Anthropic54
Claude Haiku 4.5 (Reasoning)Anthropic36

BigEarthNet.txt

Not in an index: questions on Sentinel-2 optical and Sentinel-1 radar patches · 0 to 100 · Higher is better

BigEarthNet.txtScores 0 to 100: Claude Opus 5.5 (high): 60; Claude Opus 5.5 (xhigh): 58; Claude Opus 5.5 (medium): 58; Claude Sonnet 5.5 (high): 57; Claude Sonnet 5.5 (medium): 56; Claude Sonnet 5.5 (xhigh): 56; Claude Haiku 5.5 (high): 54; Claude Opus 5 (high): 53; Claude Haiku 5.5 (xhigh): 52; Claude Haiku 5.5 (medium): 50; Claude Opus 4.7 (high): 49; Claude Opus 4.8 (high): 48; Claude Sonnet 5 (high): 47; Claude Haiku 4.5 (Reasoning): 450255075100Claude Opus 5.5 (high)60Claude Opus 5.5 (xhigh)58Claude Opus 5.5 (medium)58Claude Sonnet 5.5 (high)57Claude Sonnet 5.5 (medium)56Claude Sonnet 5.5 (xhigh)56Claude Haiku 5.5 (high)54Claude Opus 5 (high)53Claude Haiku 5.5 (xhigh)52Claude Haiku 5.5 (medium)50Claude Opus 4.7 (high)49Claude Opus 4.8 (high)48Claude Sonnet 5 (high)47Claude Haiku 4.5 (Reasoning)45
Data table: BigEarthNet.txt
BigEarthNet.txt
ModelDeveloperBigEarthNet.txt
Claude Opus 5.5 (high)Anthropic60
Claude Opus 5.5 (xhigh)Anthropic58
Claude Opus 5.5 (medium)Anthropic58
Claude Sonnet 5.5 (high)Anthropic57
Claude Sonnet 5.5 (medium)Anthropic56
Claude Sonnet 5.5 (xhigh)Anthropic56
Claude Haiku 5.5 (high)Anthropic54
Claude Opus 5 (high)Anthropic53
Claude Haiku 5.5 (xhigh)Anthropic52
Claude Haiku 5.5 (medium)Anthropic50
Claude Opus 4.7 (high)Anthropic49
Claude Opus 4.8 (high)Anthropic48
Claude Sonnet 5 (high)Anthropic47
Claude Haiku 4.5 (Reasoning)Anthropic45

Knowledge

Geospatial knowledge

Questions on geospatial knowledge · 0 to 100 · Higher is better

Geospatial knowledgeScores 0 to 100: Claude Sonnet 4.6 (high): 98; Claude Opus 5.5 (low): 98; Claude Sonnet 5.5 (low): 98; Claude Haiku 5.5 (low): 96; Claude Opus 5.5 (high): 95; Claude Opus 5.5 (xhigh): 94; Claude Sonnet 5.5 (xhigh): 94; Claude Opus 5.5 (medium): 94; Gemini 3.8 Flash (low): 94; Claude Sonnet 5.5 (high): 94; Claude Sonnet 5.5 (medium): 93; Claude Opus 4.8 (high): 93; Claude Opus 5 (high): 93; Claude Opus 4.7 (high): 93; GPT-6.1 Sol (high): 93; Claude Haiku 5.5 (high): 92; Claude Haiku 5.5 (xhigh): 92; Claude Haiku 5.5 (medium): 92; Claude Sonnet 5 (high): 91; Claude Haiku 4.5 (Reasoning): 890255075100Claude Sonnet 4.6 (high)98Claude Opus 5.5 (low)98Claude Sonnet 5.5 (low)98Claude Haiku 5.5 (low)96Claude Opus 5.5 (high)95Claude Opus 5.5 (xhigh)94Claude Sonnet 5.5 (xhigh)94Claude Opus 5.5 (medium)94Gemini 3.8 Flash (low)94Claude Sonnet 5.5 (high)94Claude Sonnet 5.5 (medium)93Claude Opus 4.8 (high)93Claude Opus 5 (high)93Claude Opus 4.7 (high)93GPT-6.1 Sol (high)93Claude Haiku 5.5 (high)92Claude Haiku 5.5 (xhigh)92Claude Haiku 5.5 (medium)92Claude Sonnet 5 (high)91Claude Haiku 4.5 (Reasoning)89
Data table: Geospatial knowledge

Cost

Cost per task

Average cost per agent task (USD) · Lower is better

  • Striped: provisional, not yet ranked
Cost per taskCost per task in US dollars: Claude Haiku 5.5 (low), Claude Code: $0.0053; Claude Haiku 5.5 (medium), Claude Code: $0.0063; Claude Haiku 5.5 (high), Claude Code: $0.0085; Claude Haiku 5.5 (xhigh), Claude Code: $0.017; Claude Sonnet 5.5 (low), Claude Code: $0.043; Claude Sonnet 5.5 (medium), Claude Code: $0.046; Claude Sonnet 5.5 (high), Claude Code: $0.055; Claude Opus 5.5 (low), Claude Code: $0.081; GPT-6.1 Sol (xhigh), Codex: $0.085; Claude Haiku 4.5 (Reasoning), Claude Code: $0.092; Claude Sonnet 5.5 (xhigh), Claude Code: $0.11; Claude Opus 5.5 (medium), Claude Code: $0.11; Claude Opus 5.5 (high), Claude Code: $0.13; Claude Sonnet 5 (high), Claude Code: $0.20; Claude Opus 5.5 (xhigh), Claude Code: $0.25; Claude Opus 4.8 (high), Claude Code: $0.26; Claude Opus 5 (high), Claude Code: $0.32; Claude Opus 4.7 (high), Claude Code: $0.34; GLM-5.3 (max), Claude Code: $0.48; Claude Sonnet 4.6 (high), Terminus-2: $0.25 (provisional, not yet ranked)$0$0.15$0.30$0.45$0.60Claude Haiku 5.5 (low)Claude Code$0.0053Claude Haiku 5.5 (medium)Claude Code$0.0063Claude Haiku 5.5 (high)Claude Code$0.0085Claude Haiku 5.5 (xhigh)Claude Code$0.017Claude Sonnet 5.5 (low)Claude Code$0.043Claude Sonnet 5.5 (medium)Claude Code$0.046Claude Sonnet 5.5 (high)Claude Code$0.055Claude Opus 5.5 (low)Claude Code$0.081GPT-6.1 Sol (xhigh)Codex$0.085Claude Haiku 4.5 (Reasoning)Claude Code$0.092Claude Sonnet 5.5 (xhigh)Claude Code$0.11Claude Opus 5.5 (medium)Claude Code$0.11Claude Opus 5.5 (high)Claude Code$0.13Claude Sonnet 5 (high)Claude Code$0.20Claude Opus 5.5 (xhigh)Claude Code$0.25Claude Opus 4.8 (high)Claude Code$0.26Claude Opus 5 (high)Claude Code$0.32Claude Opus 4.7 (high)Claude Code$0.34GLM-5.3 (max)Claude Code$0.48Claude Sonnet 4.6 (high)Terminus-2 · provisional$0.25
How to read this chart

What cost is measuring. What one attempt at a task would cost if paid token by token at the provider's published API prices, averaged over attempts: ordinary input tokens, input tokens served from the provider's cache at the lower cached price, tokens written to the cache where the provider charges for that, and output tokens (thinking included). Cost assumes each harness uses the model's pay-per-token API, priced at public list rates; sandboxes and our own engineering time are not included. Failed attempts count too.

How to read this chart. Lower is better. Costs are pay-per-token list prices, not any discount or credit a customer might have.

Bars. Every Anthropic entry with a cost, highlighted, and the top-ranked entries from other labs on the Geospatial Agent Index, faded, for context. Provisional: not yet ranked.

Data table: Cost per task

Geospatial Agent Index vs. cost per task

Geospatial Agent Index, Text only; cost per task (USD) · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
Geospatial Agent Index vs. cost per taskGeospatial Agent Index (0 to 100) against cost per task in US dollars, log scale: Claude Haiku 4.5 (Reasoning), Claude Code: 57.52, $0.092; Claude Opus 5.5 (medium), Claude Code: 80.46, $0.11; Claude Opus 5.5 (high), Claude Code: 82.41, $0.13; Claude Sonnet 5.5 (medium), Claude Code: 70.95, $0.046; Claude Sonnet 5.5 (high), Claude Code: 78.38, $0.055; Claude Haiku 5.5 (medium), Claude Code: 72.34, $0.0063; Claude Haiku 5.5 (high), Claude Code: 75.7, $0.0085; Claude Opus 5.5 (xhigh), Claude Code: 84.65, $0.25; Claude Sonnet 5.5 (xhigh), Claude Code: 79.01, $0.11; Claude Haiku 5.5 (xhigh), Claude Code: 75.72, $0.017; Claude Opus 5.5 (low), Claude Code: 73.92, $0.081; Claude Sonnet 5.5 (low), Claude Code: 69.25, $0.043; Claude Haiku 5.5 (low), Claude Code: 69.85, $0.0053; Claude Opus 5 (high), Claude Code: 79.75, $0.32; Claude Sonnet 5 (high), Claude Code: 74.37, $0.20; Claude Opus 4.8 (high), Claude Code: 75.98, $0.26; Claude Opus 4.7 (high), Claude Code: 73.56, $0.34; GPT-6.1 Sol (xhigh), Codex: 81.82, $0.085; GLM-5.3 (max), Claude Code: 73.4, $0.48; Kimi K3 (Reasoning), Terminus-2: 71.99, $0.23Most attractive quadrant505560657075808590$0.002$0.005$0.01$0.02$0.05$0.10$0.20$0.50$1.00Cost per task (USD, log scale)Geospatial Agent IndexClaude Opus 5.5 (xhigh), Claude CodeClaude Opus 5.5 (high), Claude CodeClaude Sonnet 5.5 (high), Claude CodeClaude Haiku 5.5 (xhigh), Claude CodeClaude Haiku 5.5 (high), Claude CodeClaude Haiku 5.5 (medium), Claude CodeClaude Haiku 5.5 (low), Claude CodeClaude Opus 5.5 (medium), Claude CodeClaude Opus 5 (high), Claude CodeClaude Sonnet 5.5 (xhigh), Claude CodeClaude Opus 4.8 (high), Claude CodeClaude Sonnet 5 (high), Claude CodeClaude Opus 5.5 (low), Claude CodeClaude Opus 4.7 (high), Claude CodeClaude Sonnet 5.5 (medium), Claude CodeClaude Sonnet 5.5 (low), Claude CodeClaude Haiku 4.5 (Reasoning), Claude CodeGPT-6.1 Sol (xhigh), CodexGLM-5.3 (max), Claude CodeKimi K3 (Reasoning), Terminus-2
How to read this chart

Why a log scale. Costs and times differ by a factor of ten or more between models, so equal steps on the axis are equal ratios.

What cost is measuring. What one attempt at a task would cost if paid token by token at the provider's published API prices, averaged over attempts: ordinary input tokens, input tokens served from the provider's cache at the lower cached price, tokens written to the cache where the provider charges for that, and output tokens (thinking included). Cost assumes each harness uses the model's pay-per-token API, priced at public list rates; sandboxes and our own engineering time are not included. Failed attempts count too.

How to read this chart. Each point is one entry. Further left means a lower average cost per task (log scale); higher means a higher Geospatial Agent Index. Both axes fit the models shown, so the score axis does not start at zero. The shaded most attractive quadrant is the top-left quarter of the plot, split at the middle of each axis: a reading aid that moves with the axes when you change the models shown, not a fixed bar. The dotted Pareto line joins the shown models that no cheaper shown model beats on score.

Data table: Geospatial Agent Index vs. cost per task

Time

Time per task

Average minutes per agent task, at 100 output tokens/s · Lower is better

  • Striped: provisional, not yet ranked
Time per taskTime per task: Claude Opus 5.5 (low), Claude Code: 0.4 min; Claude Sonnet 5.5 (medium), Claude Code: 0.4 min; Claude Sonnet 5.5 (low), Claude Code: 0.4 min; Claude Opus 5.5 (medium), Claude Code: 0.5 min; Claude Sonnet 5.5 (high), Claude Code: 0.6 min; Claude Opus 5.5 (high), Claude Code: 0.7 min; GPT-6.1 Sol (xhigh), Codex: 0.8 min; Claude Opus 4.8 (high), Claude Code: 0.9 min; Claude Haiku 5.5 (low), Claude Code: 0.9 min; Claude Opus 4.7 (high), Claude Code: 0.9 min; Claude Haiku 5.5 (medium), Claude Code: 1.0 min; Claude Opus 5 (high), Claude Code: 1.1 min; Claude Sonnet 5.5 (xhigh), Claude Code: 1.2 min; Claude Haiku 5.5 (high), Claude Code: 1.4 min; Claude Opus 5.5 (xhigh), Claude Code: 1.4 min; Claude Sonnet 5 (high), Claude Code: 1.5 min; Claude Haiku 4.5 (Reasoning), Claude Code: 1.6 min; Claude Haiku 5.5 (xhigh), Claude Code: 2.5 min; GLM-5.3 (max), Claude Code: 4.3 min; Claude Sonnet 4.6 (high), Terminus-2: 3.2 min (provisional, not yet ranked)01.534.56Claude Opus 5.5 (low)Claude Code0.4 minClaude Sonnet 5.5 (medium)Claude Code0.4 minClaude Sonnet 5.5 (low)Claude Code0.4 minClaude Opus 5.5 (medium)Claude Code0.5 minClaude Sonnet 5.5 (high)Claude Code0.6 minClaude Opus 5.5 (high)Claude Code0.7 minGPT-6.1 Sol (xhigh)Codex0.8 minClaude Opus 4.8 (high)Claude Code0.9 minClaude Haiku 5.5 (low)Claude Code0.9 minClaude Opus 4.7 (high)Claude Code0.9 minClaude Haiku 5.5 (medium)Claude Code1.0 minClaude Opus 5 (high)Claude Code1.1 minClaude Sonnet 5.5 (xhigh)Claude Code1.2 minClaude Haiku 5.5 (high)Claude Code1.4 minClaude Opus 5.5 (xhigh)Claude Code1.4 minClaude Sonnet 5 (high)Claude Code1.5 minClaude Haiku 4.5 (Reasoning)Claude Code1.6 minClaude Haiku 5.5 (xhigh)Claude Code2.5 minGLM-5.3 (max)Claude Code4.3 minClaude Sonnet 4.6 (high)Terminus-2 · provisional3.2 min
How to read this chart

What this metric means. Time as if every model wrote 100 output tokens per second: output tokens divided by 100, plus the time the agent's commands took. Serving speed differs between providers and is not ranked.

Bars. Every Anthropic entry with a cost, highlighted, and the top-ranked entries from other labs on the Geospatial Agent Index, faded, for context. Provisional: not yet ranked.

Data table: Time per task

Geospatial Agent Index vs. time per task

Geospatial Agent Index, Text only; time per task (minutes) · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
Geospatial Agent Index vs. time per taskGeospatial Agent Index (0 to 100) against time per task (minutes), log scale: Claude Haiku 4.5 (Reasoning), Claude Code: 57.52, 1.6 min; Claude Opus 5.5 (medium), Claude Code: 80.46, 0.5 min; Claude Opus 5.5 (high), Claude Code: 82.41, 0.7 min; Claude Sonnet 5.5 (medium), Claude Code: 70.95, 0.4 min; Claude Sonnet 5.5 (high), Claude Code: 78.38, 0.6 min; Claude Haiku 5.5 (medium), Claude Code: 72.34, 1.0 min; Claude Haiku 5.5 (high), Claude Code: 75.7, 1.4 min; Claude Opus 5.5 (xhigh), Claude Code: 84.65, 1.4 min; Claude Sonnet 5.5 (xhigh), Claude Code: 79.01, 1.2 min; Claude Haiku 5.5 (xhigh), Claude Code: 75.72, 2.5 min; Claude Opus 5.5 (low), Claude Code: 73.92, 0.4 min; Claude Sonnet 5.5 (low), Claude Code: 69.25, 0.4 min; Claude Haiku 5.5 (low), Claude Code: 69.85, 0.9 min; Claude Opus 5 (high), Claude Code: 79.75, 1.1 min; Claude Sonnet 5 (high), Claude Code: 74.37, 1.5 min; Claude Opus 4.8 (high), Claude Code: 75.98, 0.9 min; Claude Opus 4.7 (high), Claude Code: 73.56, 0.9 min; GPT-6.1 Sol (xhigh), Codex: 81.82, 0.8 min; GLM-5.3 (max), Claude Code: 73.4, 4.3 min; Kimi K3 (Reasoning), Terminus-2: 71.99, 2.7 minMost attractive quadrant5055606570758085900.2 min0.5 min1 min2 min5 minTime per task (minutes, log scale)Geospatial Agent IndexClaude Opus 5.5 (xhigh), Claude CodeClaude Opus 5.5 (high), Claude CodeClaude Opus 5.5 (medium), Claude CodeClaude Opus 5.5 (low), Claude CodeClaude Opus 5 (high), Claude CodeClaude Sonnet 5.5 (xhigh), Claude CodeClaude Sonnet 5.5 (high), Claude CodeClaude Opus 4.8 (high), Claude CodeClaude Haiku 5.5 (xhigh), Claude CodeClaude Haiku 5.5 (high), Claude CodeClaude Sonnet 5 (high), Claude CodeClaude Opus 4.7 (high), Claude CodeClaude Haiku 5.5 (medium), Claude CodeClaude Sonnet 5.5 (medium), Claude CodeClaude Haiku 5.5 (low), Claude CodeClaude Sonnet 5.5 (low), Claude CodeClaude Haiku 4.5 (Reasoning), Claude CodeGPT-6.1 Sol (xhigh), CodexGLM-5.3 (max), Claude CodeKimi K3 (Reasoning), Terminus-2
How to read this chart

Why a log scale. Costs and times differ by a factor of ten or more between models, so equal steps on the axis are equal ratios.

What this metric means. Time as if every model wrote 100 output tokens per second: output tokens divided by 100, plus the time the agent's commands took. Serving speed differs between providers and is not ranked.

How to read this chart. Each point is one entry. Further left means a lower average time per task (log scale); higher means a higher Geospatial Agent Index. Both axes fit the models shown, so the score axis does not start at zero. The shaded most attractive quadrant is the top-left quarter of the plot, split at the middle of each axis: a reading aid that moves with the axes when you change the models shown, not a fixed bar. The dotted Pareto line joins the shown models that no faster shown model beats on score.

Data table: Geospatial Agent Index vs. time per task

Every benchmark

Score by benchmark

Share answered correctly, 0 to 100 · Darker is better; hatched: provisional, evaluation not finished

Data table: Score by benchmark
Every benchmark
ModelStatusEarth-Bench V2GeoBenchXGS-QA2GeoAgentBenchGeoAnalystBenchOGD4AllGeoNatureAgentMultiGlobeQAGeoAgentEvalThinkGeoOpenEarthAgentEarth-Bench V2 imagesThinkGeo imagesGeoChronoBigEarthNet.txtGeospatial knowledge
Claude Opus 5.5 (xhigh), Claude CodeRanked778394981009610079100961007048745894
Claude Opus 5.5 (high), Claude CodeRanked797990100100951007810087947444736095
Claude Opus 5.5 (medium), Claude CodeRanked72799098959710078100871007044No data5894
Claude Opus 5 (high), Claude CodeRanked74759110089951007996811006838715393
Claude Sonnet 5.5 (xhigh), Claude CodeRanked6881879895971007910089886847765694
Claude Sonnet 5.5 (high), Claude CodeRanked71818398100961007710074886850745794
Claude Opus 4.8 (high), Claude CodeRanked7173849610097100759268886634594893
Claude Haiku 5.5 (xhigh), Claude CodeRanked6877811009597100759274947035No data5292
Claude Haiku 5.5 (high), Claude CodeRanked727283988496100749262946035685492
Claude Sonnet 5 (high), Claude CodeRanked687777989595100739281826628554791
Claude Opus 5.5 (low), Claude CodeRanked59778696100951007810085100No dataNo dataNo dataNo data98
Claude Opus 4.7 (high), Claude CodeRanked6973799610095100779272886827544993
Claude Haiku 5.5 (medium), Claude CodeRanked687179949595100739270945635No data5092
Claude Sonnet 5.5 (medium), Claude CodeRanked5876799895961007496771006843No data5693
Claude Haiku 5.5 (low), Claude CodeRanked627375921009510072927094No dataNo dataNo dataNo data96
Claude Sonnet 5.5 (low), Claude CodeRanked5677769495961007510070100No dataNo dataNo dataNo data98
Claude Haiku 4.5 (Reasoning), Claude CodeRanked51536978749593708817245019364589
Claude Sonnet 4.6 (high), Terminus-2Provisional59 (provisional)57No data96100No dataNo dataNo dataNo dataNo dataNo dataNo dataNo dataNo dataNo data98

Frequently asked questions

What Anthropic models do you benchmark?
Which is the most intelligent Anthropic model for geospatial work?
Claude Opus 5.5 (xhigh), with 88.7 on the Geospatial Intelligence Index (Text only), #1 of 61.
What is the cheapest Anthropic model per task?
Claude Haiku 5.5 (low), Claude Code, at $0.0053 per agent task at list prices, #5 of 74 on the Geospatial Agent Index.
What is the fastest Anthropic model?
Claude Opus 5.5 (low), Claude Code, at 0.4 min per agent task at 100 output tokens per second, #1 of 74.
Does Anthropic offer open-weights models?
No. Every Anthropic model we benchmark is available only through an API.
Which Anthropic models can read satellite imagery?
How do Anthropic models do on Earth observation, GIS and geospatial knowledge?
Which Anthropic model is best for agent work, and in which harness?
Claude Opus 5.5 (xhigh), Claude Code, with 84.7 on the Geospatial Agent Index, #1 of 74, in the Claude Code harness.
How does Anthropic's best model compare with the overall leader?
Are any Anthropic models still being benchmarked?
Yes. Claude Sonnet 4.6 (high), Terminus-2 is still being benchmarked, so their results are provisional: not yet ranked.
How should I choose between Anthropic models for geospatial work?
Start from the job. For the strongest answers, Claude Opus 5.5 (xhigh); for agent work with data and code, Claude Opus 5.5 (xhigh), Claude Code; for the lowest cost, Claude Haiku 5.5 (low), Claude Code; for reading imagery, Claude Opus 5.5 (high). Each model page shows its scores on every evaluation.