Axis Spatial

ThinkGeo images benchmark leaderboard

Questions on aerial and satellite images, answered from the image alone, with no tools. One of the two sources of Vision, a group of the Geospatial Intelligence Index. The same questions worked out by an agent that can run code are in Vision agents.

Score

ThinkGeo images score

Share of questions answered correctly, 0 to 100 · Higher is better

ThinkGeo images scoreScores 0 to 100: Claude Opus 5.5 (xhigh): 48; Claude Sonnet 5.5 (xhigh): 47; GPT-5.6 Sol (high): 41; GPT-6 Sol (high): 41; GPT-6.1 Sol (xhigh): 41; Claude Opus 5 (high): 38; GPT-5.6 Luna (xhigh): 37; Qwen 3.8 27B (xhigh): 37; Claude Haiku 5.5 (xhigh): 35; GLM-5.3-Flash (max): 35; GPT-6 Luna (xhigh): 35; Claude Opus 4.8 (high): 34; GPT-5.6 Terra (high): 34; Gemini 3.8 Flash (low): 34; Kimi K2.7 Code (Reasoning): 31; Kimi K3 (Reasoning): 30; Claude Sonnet 5 (high): 28; Kimi K2.6 (Reasoning): 28; Claude Opus 4.7 (high): 27; Gemini 3.1 Flash-Lite (high): 24; Gemma 4 26B A4B (Reasoning): 22; Claude Haiku 4.5 (Reasoning): 19; Mistral Large 3 (Non-reasoning): 150255075100Claude Opus 5.5 (xhigh)48Claude Sonnet 5.5 (xhigh)47GPT-5.6 Sol (high)41GPT-6 Sol (high)41GPT-6.1 Sol (xhigh)41Claude Opus 5 (high)38GPT-5.6 Luna (xhigh)37Qwen 3.8 27B (xhigh)37Claude Haiku 5.5 (xhigh)35GLM-5.3-Flash (max)35GPT-6 Luna (xhigh)35Claude Opus 4.8 (high)34GPT-5.6 Terra (high)34Gemini 3.8 Flash (low)34Kimi K2.7 Code (Reasoning)31Kimi K3 (Reasoning)30Claude Sonnet 5 (high)28Kimi K2.6 (Reasoning)28Claude Opus 4.7 (high)27Gemini 3.1 Flash-Lite (high)24Gemma 4 26B A4B (Reasoning)22Claude Haiku 4.5 (Reasoning)19Mistral Large 3 (Non-reasoning)15
How to read this chart

What this metric means. The share of questions the model answered correctly from the image alone, with no tools.

Rows. Each model once, at its highest reasoning level with a score; every level is in the data table.

Data table: ThinkGeo images score
ThinkGeo images score
ModelThinkGeo images scoreCost per questionTime per question (at 100 output tokens/s)
Claude Sonnet 5.5 (high)50$0.00707s
Claude Opus 5.5 (xhigh)48$0.02613s
Claude Sonnet 5.5 (xhigh)47$0.01011s
Claude Opus 5.5 (high)44$0.0169s
Claude Opus 5.5 (medium)44$0.0298s
Claude Sonnet 5.5 (medium)43$0.0115s
GPT-6 Luna (high)43No dataNo data
GPT-5.6 Sol (high)41No dataNo data
GPT-6 Sol (high)41No dataNo data
GPT-6.1 Sol (xhigh)41$0.03836s
Claude Opus 5 (high)38$0.04712s
GPT-5.6 Luna (xhigh)37No dataNo data
GPT-6 Luna (medium)37No dataNo data
GPT-6.1 Sol (high)37$0.01411s
GPT-6.1 Sol (medium)37$0.00876s
Qwen 3.8 27B (xhigh) Open weights37No dataNo data
GLM-5.3-Flash (low) Open weights36$0.000386s
Claude Haiku 5.5 (high)35$0.0009812s
Claude Haiku 5.5 (medium)35$0.0005310s
Claude Haiku 5.5 (xhigh)35$0.0009518s
GLM-5.3-Flash (max) Open weights35$0.0066126s
GPT-5.6 Luna (high)35No dataNo data
GPT-5.6 Luna (medium)35No dataNo data
GPT-6 Luna (xhigh)35$0.001324s
Claude Opus 4.8 (high)34$0.0347s
GPT-5.6 Terra (high)34No dataNo data
Gemini 3.8 Flash (low)34No dataNo data
GPT-5.6 Luna (low)33No dataNo data
Kimi K2.7 Code (Reasoning) Open weights31$0.075187s
Kimi K3 (Reasoning) Open weights30No dataNo data
GPT-6 Luna (low)29No dataNo data
Claude Sonnet 5 (high)28$0.02314s
Kimi K2.6 (Reasoning) Open weights28$0.084208s
Claude Opus 4.7 (high)27$0.0388s
Gemini 3.1 Flash-Lite (minimal)26No dataNo data
Gemini 3.1 Flash-Lite (high)24No dataNo data
Gemma 4 26B A4B (Reasoning) Open weights22$0.0041138s
Claude Haiku 4.5 (Reasoning)19$0.02548s
Gemini 3.1 Flash-Lite (low)15No dataNo data
Mistral Large 3 (Non-reasoning) Open weights15No dataNo data
Mistral Small 3.1 24B (Non-reasoning) Open weights12$0.000845s

ThinkGeo images: score vs. cost per question

ThinkGeo images score against average cost per question (USD) · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
ThinkGeo images: score vs. cost per questionThinkGeo images score (0 to 100) against cost per question in US dollars, log scale: Claude Opus 5.5 (xhigh): 47.67, $0.026; Claude Sonnet 5.5 (xhigh): 46.51, $0.010; GPT-6.1 Sol (xhigh): 40.7, $0.038; Claude Opus 5 (high): 38.37, $0.047; Claude Haiku 5.5 (xhigh): 34.88, $0.00095; GLM-5.3-Flash (max): 34.88, $0.0066; GPT-6 Luna (xhigh): 34.88, $0.0013; Claude Opus 4.8 (high): 33.72, $0.034; Kimi K2.7 Code (Reasoning): 31.4, $0.075; Claude Sonnet 5 (high): 27.91, $0.023; Kimi K2.6 (Reasoning): 27.91, $0.084; Claude Opus 4.7 (high): 26.74, $0.038; Gemma 4 26B A4B (Reasoning): 22.35, $0.0041; Claude Haiku 4.5 (Reasoning): 18.6, $0.025Most attractive quadrant152025303540455055$0.0005$0.001$0.002$0.005$0.01$0.02$0.05$0.10Cost per question (USD, log scale)ThinkGeo images scoreClaude Opus 5.5 (xhigh)Claude Sonnet 5.5 (xhigh)Claude Haiku 5.5 (xhigh)GPT-6.1 Sol (xhigh)Claude Opus 5 (high)GLM-5.3-Flash (max)GPT-6 Luna (xhigh)Claude Opus 4.8 (high)Kimi K2.7 Code (Reasoning)Claude Sonnet 5 (high)Kimi K2.6 (Reasoning)Claude Opus 4.7 (high)Gemma 4 26B A4B (Reasoning)Claude Haiku 4.5 (Reasoning)
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. Each point is one entry. Further left means a lower average cost per question (log scale); higher means a higher ThinkGeo images score. Both axes fit the points 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, not a fixed bar. The dotted Pareto line joins the points that no cheaper one beats on score. Only exact costs are plotted; the table lists every entry.

Data table: ThinkGeo images: score vs. cost per question
ThinkGeo images: score vs. cost per question
ModelThinkGeo images scoreCost per question (USD)On the Pareto line
Claude Opus 5.5 (xhigh)48$0.026Yes
Claude Sonnet 5.5 (xhigh)47$0.010Yes
GPT-5.6 Sol (high)41No dataNo data
GPT-6 Sol (high)41No dataNo data
GPT-6.1 Sol (xhigh)41$0.038No
Claude Opus 5 (high)38$0.047No
GPT-5.6 Luna (xhigh)37No dataNo data
Qwen 3.8 27B (xhigh)37No dataNo data
Claude Haiku 5.5 (xhigh)35$0.00095Yes
GLM-5.3-Flash (max)35$0.0066No
GPT-6 Luna (xhigh)35$0.0013No
Claude Opus 4.8 (high)34$0.034No
GPT-5.6 Terra (high)34No dataNo data
Gemini 3.8 Flash (low)34No dataNo data
Kimi K2.7 Code (Reasoning)31$0.075No
Kimi K3 (Reasoning)30No dataNo data
Claude Sonnet 5 (high)28$0.023No
Kimi K2.6 (Reasoning)28$0.084No
Claude Opus 4.7 (high)27$0.038No
Gemini 3.1 Flash-Lite (high)24No dataNo data
Gemma 4 26B A4B (Reasoning)22$0.0041No
Claude Haiku 4.5 (Reasoning)19$0.025No
Mistral Large 3 (Non-reasoning)15No dataNo data

Token usage

ThinkGeo images: tokens per question

Average tokens per question by type · Lower is better

  • Uncached input
  • Cached input
  • Output (reasoning included)
ThinkGeo images: tokens per questionClaude Opus 4.8 (high): 3k; Claude Sonnet 5.5 (xhigh): 3k; Claude Opus 4.7 (high): 3k; Claude Opus 5 (high): 3k; Claude Opus 5.5 (xhigh): 3k; Claude Sonnet 5 (high): 4k; GPT-6 Luna (xhigh): 4k; Claude Haiku 5.5 (xhigh): 4k; GPT-6.1 Sol (xhigh): 5k; Claude Haiku 4.5 (Reasoning): 7k; Gemma 4 26B A4B (Reasoning): 14k; GLM-5.3-Flash (max): 14k; Kimi K2.7 Code (Reasoning): 20k; Kimi K2.6 (Reasoning): 22k010k20k30k40kClaude Opus 4.8 (high)3kClaude Sonnet 5.5 (xhigh)3kClaude Opus 4.7 (high)3kClaude Opus 5 (high)3kClaude Opus 5.5 (xhigh)3kClaude Sonnet 5 (high)4kGPT-6 Luna (xhigh)4kClaude Haiku 5.5 (xhigh)4kGPT-6.1 Sol (xhigh)5kClaude Haiku 4.5 (Reasoning)7kGemma 4 26B A4B (Reasoning)14kGLM-5.3-Flash (max)14kKimi K2.7 Code (Reasoning)20kKimi K2.6 (Reasoning)22k
How to read this chart

What the parts mean. Uncached input: input tokens read at the full price. Cached input: input tokens served from the provider's cache at the lower cached price. Output: the tokens the model wrote, its reasoning included, as reported by the provider.

Compare with care. Models use different tokenisers, so the same text is a different number of tokens for different models. Use token counts to see how much work each model did, and cost to compare spending.

Data table: ThinkGeo images: tokens per question
ThinkGeo images: tokens per question
ModelDeveloperUncached inputCached inputOutput (reasoning included)Total
Claude Opus 4.8 (high)Anthropic2kNo data5543k
Claude Sonnet 5.5 (xhigh)Anthropic1772k9493k
Claude Opus 4.7 (high)Anthropic2kNo data6723k
Claude Opus 5 (high)Anthropic2kNo data1k3k
Claude Opus 5.5 (xhigh)Anthropic1732k1k3k
Claude Sonnet 5 (high)Anthropic2kNo data1k4k
GPT-6 Luna (xhigh)OpenAI2kNo data2k4k
Claude Haiku 5.5 (xhigh)Anthropic4492k2k4k
GPT-6.1 Sol (xhigh)OpenAI2kNo data3k5k
Claude Haiku 4.5 (Reasoning)Anthropic2kNo data5k7k
Gemma 4 26B A4B (Reasoning)Google564013k14k
GLM-5.3-Flash (max)Z.ai2k3312k14k
Kimi K2.7 Code (Reasoning)Moonshot AI2421k19k20k
Kimi K2.6 (Reasoning)Moonshot AI1k23921k22k
GPT-5.6 Sol (high)OpenAINo dataNo dataNo dataNo data
GPT-6 Sol (high)OpenAINo dataNo dataNo dataNo data
GPT-5.6 Luna (xhigh)OpenAINo dataNo dataNo dataNo data
Qwen 3.8 27B (xhigh)Alibaba (Qwen)No dataNo dataNo dataNo data
GPT-5.6 Terra (high)OpenAINo dataNo dataNo dataNo data
Gemini 3.8 Flash (low)GoogleNo dataNo dataNo dataNo data
Kimi K3 (Reasoning)Moonshot AINo dataNo dataNo dataNo data
Gemini 3.1 Flash-Lite (high)GoogleNo dataNo dataNo dataNo data
Mistral Large 3 (Non-reasoning)Mistral AINo dataNo dataNo dataNo data

Cost

ThinkGeo images: cost per question

Average cost per question (USD) by token type · Lower is better

  • Uncached input
  • Cached input
  • Output
  • Not split by token type
ThinkGeo images: cost per questionValues in US dollars: Claude Haiku 5.5 (xhigh): $0.00095; GPT-6 Luna (xhigh): $0.0013; Gemma 4 26B A4B (Reasoning): $0.0041; GLM-5.3-Flash (max): $0.0066; Claude Sonnet 5.5 (xhigh): $0.010; Claude Sonnet 5 (high): $0.023; Claude Haiku 4.5 (Reasoning): $0.025; Claude Opus 5.5 (xhigh): $0.026; Claude Opus 4.8 (high): $0.034; GPT-6.1 Sol (xhigh): $0.038; Claude Opus 4.7 (high): $0.038; Claude Opus 5 (high): $0.047; Kimi K2.7 Code (Reasoning): $0.075; Kimi K2.6 (Reasoning): $0.084$0$0.025$0.05$0.075$0.10Claude Haiku 5.5 (xhigh)$0.00095GPT-6 Luna (xhigh)$0.0013Gemma 4 26B A4B (Reasoning)$0.0041GLM-5.3-Flash (max)$0.0066Claude Sonnet 5.5 (xhigh)$0.010Claude Sonnet 5 (high)$0.023Claude Haiku 4.5 (Reasoning)$0.025Claude Opus 5.5 (xhigh)$0.026Claude Opus 4.8 (high)$0.034GPT-6.1 Sol (xhigh)$0.038Claude Opus 4.7 (high)$0.038Claude Opus 5 (high)$0.047Kimi K2.7 Code (Reasoning)$0.075Kimi K2.6 (Reasoning)$0.084
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 the cost is split. Each part is the entry's average tokens of that type times its list price. The rest, mostly tokens written to the cache, is shown as not split by token type.

Data table: ThinkGeo images: cost per question
ThinkGeo images: cost per question
ModelDeveloperUncached inputCached inputOutputNot split by token typeTotal
Claude Haiku 5.5 (xhigh)Anthropic$0.000045$0.000018$0.00084$0.000044$0.00095
GPT-6 Luna (xhigh)OpenAI$0.00016$0.00$0.0011$0.00$0.0013
Gemma 4 26B A4B (Reasoning)Google$0.000056$0.00$0.0040$0.00000019$0.0041
GLM-5.3-Flash (max)Z.ai$0.00025$0.00000098$0.0062$0.000076$0.0066
Claude Sonnet 5.5 (xhigh)Anthropic$0.00035$0.00018$0.0095$0.00035$0.010
Claude Sonnet 5 (high)Anthropic$0.0048$0.00$0.013$0.0048$0.023
Claude Haiku 4.5 (Reasoning)Anthropic$0.0020$0.00$0.023$0.00000010$0.025
Claude Opus 5.5 (xhigh)Anthropic$0.00069$0.00037$0.024$0.00069$0.026
Claude Opus 4.8 (high)Anthropic$0.010$0.00$0.014$0.0098$0.034
GPT-6.1 Sol (xhigh)OpenAI$0.0032$0.00$0.035$0.00$0.038
Claude Opus 4.7 (high)Anthropic$0.012$0.00$0.017$0.0094$0.038
Claude Opus 5 (high)Anthropic$0.010$0.00$0.027$0.010$0.047
Kimi K2.7 Code (Reasoning)Moonshot AI$0.00023$0.00028$0.074$0.000000068$0.075
Kimi K2.6 (Reasoning)Moonshot AI$0.0014$0.000038$0.083$0.000000017$0.084
GPT-5.6 Sol (high)OpenAINo dataNo dataNo dataNo dataNo data
GPT-6 Sol (high)OpenAINo dataNo dataNo dataNo dataNo data
GPT-5.6 Luna (xhigh)OpenAINo dataNo dataNo dataNo dataNo data
Qwen 3.8 27B (xhigh)Alibaba (Qwen)No dataNo dataNo dataNo dataNo data
GPT-5.6 Terra (high)OpenAINo dataNo dataNo dataNo dataNo data
Gemini 3.8 Flash (low)GoogleNo dataNo dataNo dataNo dataNo data
Kimi K3 (Reasoning)Moonshot AINo dataNo dataNo dataNo dataNo data
Gemini 3.1 Flash-Lite (high)GoogleNo dataNo dataNo dataNo dataNo data
Mistral Large 3 (Non-reasoning)Mistral AINo dataNo dataNo dataNo dataNo data

Speed

ThinkGeo images: time per question

Time per question (at 100 output tokens/s), seconds · Lower is better

ThinkGeo images: time per questionThinkGeo images: time per question: Claude Opus 4.8 (high): 7s; Claude Opus 4.7 (high): 8s; Claude Sonnet 5.5 (xhigh): 11s; Claude Opus 5 (high): 12s; Claude Opus 5.5 (xhigh): 13s; Claude Sonnet 5 (high): 14s; Claude Haiku 5.5 (xhigh): 18s; GPT-6 Luna (xhigh): 24s; GPT-6.1 Sol (xhigh): 36s; Claude Haiku 4.5 (Reasoning): 48s; GLM-5.3-Flash (max): 126s; Gemma 4 26B A4B (Reasoning): 138s; Kimi K2.7 Code (Reasoning): 187s; Kimi K2.6 (Reasoning): 208s; GPT-5.6 Sol (high): No data; GPT-6 Sol (high): No data; GPT-5.6 Luna (xhigh): No data; Qwen 3.8 27B (xhigh): No data; GPT-5.6 Terra (high): No data; Gemini 3.8 Flash (low): No data; Kimi K3 (Reasoning): No data; Gemini 3.1 Flash-Lite (high): No data; Mistral Large 3 (Non-reasoning): No data0s100s200s300s400sClaude Opus 4.8 (high)7sClaude Opus 4.7 (high)8sClaude Sonnet 5.5 (xhigh)11sClaude Opus 5 (high)12sClaude Opus 5.5 (xhigh)13sClaude Sonnet 5 (high)14sClaude Haiku 5.5 (xhigh)18sGPT-6 Luna (xhigh)24sGPT-6.1 Sol (xhigh)36sClaude Haiku 4.5 (Reasoning)48sGLM-5.3-Flash (max)126sGemma 4 26B A4B (Reasoning)138sKimi K2.7 Code (Reasoning)187sKimi K2.6 (Reasoning)208s
How to read this chart

Time per question. 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.

Data table: ThinkGeo images: time per question
ThinkGeo images: time per question
ModelDeveloperTime per question (s)
Claude Opus 4.8 (high)Anthropic7s
Claude Opus 4.7 (high)Anthropic8s
Claude Sonnet 5.5 (xhigh)Anthropic11s
Claude Opus 5 (high)Anthropic12s
Claude Opus 5.5 (xhigh)Anthropic13s
Claude Sonnet 5 (high)Anthropic14s
Claude Haiku 5.5 (xhigh)Anthropic18s
GPT-6 Luna (xhigh)OpenAI24s
GPT-6.1 Sol (xhigh)OpenAI36s
Claude Haiku 4.5 (Reasoning)Anthropic48s
GLM-5.3-Flash (max)Z.ai126s
Gemma 4 26B A4B (Reasoning)Google138s
Kimi K2.7 Code (Reasoning)Moonshot AI187s
Kimi K2.6 (Reasoning)Moonshot AI208s
GPT-5.6 Sol (high)OpenAINo data
GPT-6 Sol (high)OpenAINo data
GPT-5.6 Luna (xhigh)OpenAINo data
Qwen 3.8 27B (xhigh)Alibaba (Qwen)No data
GPT-5.6 Terra (high)OpenAINo data
Gemini 3.8 Flash (low)GoogleNo data
Kimi K3 (Reasoning)Moonshot AINo data
Gemini 3.1 Flash-Lite (high)GoogleNo data
Mistral Large 3 (Non-reasoning)Mistral AINo data

ThinkGeo images: score vs. time per question

ThinkGeo images score against time per question (at 100 output tokens/s), seconds · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
ThinkGeo images: score vs. time per questionThinkGeo images score (0 to 100) against time per question (seconds), log scale: Claude Opus 5.5 (xhigh): 47.67, 13s; Claude Sonnet 5.5 (xhigh): 46.51, 11s; GPT-6.1 Sol (xhigh): 40.7, 36s; Claude Opus 5 (high): 38.37, 12s; Claude Haiku 5.5 (xhigh): 34.88, 18s; GLM-5.3-Flash (max): 34.88, 126s; GPT-6 Luna (xhigh): 34.88, 24s; Claude Opus 4.8 (high): 33.72, 7s; Kimi K2.7 Code (Reasoning): 31.4, 187s; Claude Sonnet 5 (high): 27.91, 14s; Kimi K2.6 (Reasoning): 27.91, 208s; Claude Opus 4.7 (high): 26.74, 8s; Gemma 4 26B A4B (Reasoning): 22.35, 138s; Claude Haiku 4.5 (Reasoning): 18.6, 48sMost attractive quadrant1520253035404550555s10s20s50s100s200s500sTime per question (seconds, log scale)ThinkGeo images scoreClaude Opus 5.5 (xhigh)Claude Sonnet 5.5 (xhigh)GPT-6.1 Sol (xhigh)Claude Opus 4.8 (high)Claude Opus 5 (high)Claude Haiku 5.5 (xhigh)GLM-5.3-Flash (max)GPT-6 Luna (xhigh)Kimi K2.7 Code (Reasoning)Claude Sonnet 5 (high)Kimi K2.6 (Reasoning)Claude Opus 4.7 (high)Gemma 4 26B A4B (Reasoning)Claude Haiku 4.5 (Reasoning)
How to read this chart

Time per question. 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 question (log scale); higher means a higher ThinkGeo images score. Both axes fit the points shown, so the score axis does not start at zero. The shaded most attractive quadrant is the top-left quarter of the plot: a reading aid, not a fixed bar. The dotted Pareto line joins the points that no faster one beats on score.

Data table: ThinkGeo images: score vs. time per question
ThinkGeo images: score vs. time per question
ModelThinkGeo images scoreTime per question (seconds)On the Pareto line
Claude Opus 5.5 (xhigh)4813sYes
Claude Sonnet 5.5 (xhigh)4711sYes
GPT-5.6 Sol (high)41No dataNo data
GPT-6 Sol (high)41No dataNo data
GPT-6.1 Sol (xhigh)4136sNo
Claude Opus 5 (high)3812sNo
GPT-5.6 Luna (xhigh)37No dataNo data
Qwen 3.8 27B (xhigh)37No dataNo data
Claude Haiku 5.5 (xhigh)3518sNo
GLM-5.3-Flash (max)35126sNo
GPT-6 Luna (xhigh)3524sNo
Claude Opus 4.8 (high)347sYes
GPT-5.6 Terra (high)34No dataNo data
Gemini 3.8 Flash (low)34No dataNo data
Kimi K2.7 Code (Reasoning)31187sNo
Kimi K3 (Reasoning)30No dataNo data
Claude Sonnet 5 (high)2814sNo
Kimi K2.6 (Reasoning)28208sNo
Claude Opus 4.7 (high)278sNo
Gemini 3.1 Flash-Lite (high)24No dataNo data
Gemma 4 26B A4B (Reasoning)22138sNo
Claude Haiku 4.5 (Reasoning)1948sNo
Mistral Large 3 (Non-reasoning)15No dataNo data

Score vs. release date

ThinkGeo images: score vs. release date

ThinkGeo images score against the model's public release date

ThinkGeo images: score vs. release dateThinkGeo images score (0 to 100) against release date: Claude Opus 5.5 (xhigh): 47.67, 22 September 2026; Claude Sonnet 5.5 (xhigh): 46.51, 28 September 2026; GPT-6.1 Sol (xhigh): 40.7, 29 September 2026; Claude Opus 5 (high): 38.37, 24 July 2026; Qwen 3.8 27B (xhigh): 36.71, 14 August 2026; Claude Haiku 5.5 (xhigh): 34.88, 7 October 2026; GLM-5.3-Flash (max): 34.88, 26 August 2026; GPT-6 Luna (xhigh): 34.88, 22 September 2026; Claude Opus 4.8 (high): 33.72, 28 May 2026; Gemini 3.8 Flash (low): 33.72, 2 September 2026; Kimi K2.7 Code (Reasoning): 31.4, 12 June 2026; Kimi K3 (Reasoning): 30.23, 16 July 2026; Claude Sonnet 5 (high): 27.91, 30 June 2026; Kimi K2.6 (Reasoning): 27.91, 20 April 2026; Claude Opus 4.7 (high): 26.74, 16 April 2026; Gemini 3.1 Flash-Lite (high): 24.42, 7 May 2026; Gemma 4 26B A4B (Reasoning): 22.35, 2 April 2026; Claude Haiku 4.5 (Reasoning): 18.6, 15 October 2025; Mistral Large 3 (Non-reasoning): 15.12, 2 December 202510152025303540455055Oct 2025Jan 2026Apr 2026Jul 2026Oct 2026Jan 2027Release dateThinkGeo images scoreClaude Opus 5.5 (xhigh)Claude Sonnet 5.5 (xhigh)GPT-6.1 Sol (xhigh)Claude Opus 5 (high)Qwen 3.8 27B (xhigh)Claude Haiku 5.5 (xhigh)GLM-5.3-Flash (max)GPT-6 Luna (xhigh)Claude Opus 4.8 (high)Gemini 3.8 Flash (low)Kimi K2.7 Code (Reasoning)Kimi K3 (Reasoning)Claude Sonnet 5 (high)Kimi K2.6 (Reasoning)Claude Opus 4.7 (high)Gemini 3.1 Flash-Lite (high)Gemma 4 26B A4B (Reasoning)Claude Haiku 4.5 (Reasoning)Mistral Large 3 (Non-reasoning)
How to read this chart

How to read this chart. Each point is one entry: across, the date its model was first released; up, its ThinkGeo images score. Models with no published release date are not plotted.

Data table: ThinkGeo images: score vs. release date
ThinkGeo images: score vs. release date
ModelThinkGeo images scoreRelease date
Claude Opus 5.5 (xhigh)4822 September 2026
Claude Sonnet 5.5 (xhigh)4728 September 2026
GPT-5.6 Sol (high)41No data
GPT-6 Sol (high)41No data
GPT-6.1 Sol (xhigh)4129 September 2026
Claude Opus 5 (high)3824 July 2026
GPT-5.6 Luna (xhigh)37No data
Qwen 3.8 27B (xhigh)3714 August 2026
Claude Haiku 5.5 (xhigh)357 October 2026
GLM-5.3-Flash (max)3526 August 2026
GPT-6 Luna (xhigh)3522 September 2026
Claude Opus 4.8 (high)3428 May 2026
GPT-5.6 Terra (high)34No data
Gemini 3.8 Flash (low)342 September 2026
Kimi K2.7 Code (Reasoning)3112 June 2026
Kimi K3 (Reasoning)3016 July 2026
Claude Sonnet 5 (high)2830 June 2026
Kimi K2.6 (Reasoning)2820 April 2026
Claude Opus 4.7 (high)2716 April 2026
Gemini 3.1 Flash-Lite (high)247 May 2026
Gemma 4 26B A4B (Reasoning)222 April 2026
Claude Haiku 4.5 (Reasoning)1915 October 2025
Mistral Large 3 (Non-reasoning)152 December 2025

Background

ThinkGeo asks for one number about aerial and satellite images: a count, an area, a distance or a heading, accepted within a range.

Licence: CC BY 4.0, with the terms of the source imagery.

Published by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).

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