Axis Spatial

MultiGlobeQA benchmark leaderboard

Spatial reasoning over facts about places worldwide, from MultiGlobeQA. A standalone evaluation: its scores are shown here and on model pages, but it is not counted in any index or ranking until more models have run it.

Score

MultiGlobeQA score

Share of tasks passed, 0 to 100 · Higher is better

MultiGlobeQA scoreScores 0 to 100: Claude Sonnet 5.5 (xhigh), Claude Code: 80; Claude Opus 5.5 (xhigh), Claude Code: 79; Claude Opus 5 (high), Claude Code: 79; Claude Opus 5.5 (medium), Claude Code: 79; Claude Opus 5.5 (high), Claude Code: 78; Claude Opus 4.7 (high), Claude Code: 77; Claude Sonnet 5.5 (high), Claude Code: 77; Claude Sonnet 5.5 (medium), Claude Code: 76; Claude Haiku 5.5 (xhigh), Claude Code: 76; Claude Opus 4.8 (high), Claude Code: 75; Claude Haiku 5.5 (high), Claude Code: 74; Claude Sonnet 5 (high), Claude Code: 73; Claude Haiku 5.5 (medium), Claude Code: 73; Claude Haiku 4.5 (Reasoning), Claude Code: 70; Claude Sonnet 4.6 (high), Terminus-2: No data; DeepSeek V4 Flash (max), Terminus-2: No data; DeepSeek V4 Flash (high), Terminus-2: No data; DeepSeek V4 Pro (max), Terminus-2: No data; DeepSeek V4 Pro (high), Terminus-2: No data; Gemini 3.1 Flash-Lite (low), Terminus-2: No data; Gemini 3.1 Flash-Lite (minimal), Terminus-2: No data; Gemini 3.1 Flash-Lite (high), Terminus-2: No data; Gemini 3.1 Pro (preview) (low), Terminus-2: No data; Gemini 3.1 Pro (preview) (high), Terminus-2: No data; Gemini 3.8 Flash (high), Terminus-2: No data; Gemini 3.8 Flash (low), Terminus-2: No data; Gemma 4 26B A4B (Reasoning), Terminus-2: No data; GLM-4.7-Flash (Reasoning), Terminus-2: No data; GLM-5.2 (high), Terminus-2: No data; GLM-5.2 (Non-reasoning), Terminus-2: No data; GLM-5.2 (max), Terminus-2: No data; GLM-5.3-Flash (low), Terminus-2: No data; GLM-5.3-Flash (max), Terminus-2: No data; GLM-5.3 (low), Terminus-2: No data; GLM-5.3 (max), Terminus-2: No data; gpt-oss-120b (low), Terminus-2: No data; gpt-oss-120b (high), Terminus-2: No data; gpt-oss-20b (high), Terminus-2: No data; Kimi K2.6 (Reasoning), Terminus-2: No data; Kimi K2.7 Code (Reasoning), Terminus-2: No data; Kimi K3 (Reasoning), Terminus-2: No data; Llama 3.3 70B (Non-reasoning), Terminus-2: No data; MiniMax M3.1 Flash (max), Terminus-2: No data; Mistral Large 3 (Non-reasoning), Terminus-2: No data; Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2: No data; Nemotron 3 Ultra (high), Terminus-2: No data; Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: No data; Qwen 3.8 27B (xhigh), Terminus-2: No data; GLM-4.7-Flash (Reasoning), Claude Code: No data; GLM-5.2 (max), Claude Code: No data; GLM-5.3-Flash (max), Claude Code: No data; GLM-5.3 (max), Claude Code: No data; DeepSeek V4 Flash (high), Codex: No data; DeepSeek V4 Pro (high), Codex: No data; DeepSeek V4.1 Flash (max), Codex: No data; gpt-oss-120b (high), Codex: No data; gpt-oss-20b (high), Codex: No data; Kimi K2.6 (Reasoning), Kimi Code: No data; Kimi K2.7 Code (Reasoning), Kimi Code: No data; Qwen 3.8 27B (xhigh), Qwen Code: No data; GPT-6.1 Sol (medium), Codex: No data; GPT-6.1 Sol (high), Codex: No data; GPT-6.1 Sol (xhigh), Codex: No data; GPT-6 Luna (xhigh), Codex: No data; GPT-6 Sol (medium), Codex: No data; GPT-6 Sol (high), Codex: No data; GPT-6 Luna (medium), Codex: No data; GPT-6 Luna (high), Codex: No data; GPT-5.6 Sol (medium), Codex: No data; GPT-5.6 Sol (high), Codex: No data; GPT-5.6 Terra (high), Codex: No data; GPT-5.6 Luna (medium), Codex: No data; GPT-5.6 Luna (high), Codex: No data; GPT-5.6 Luna (xhigh), Codex: No data; GPT-6 Luna (low), Codex: No data; GPT-5.6 Luna (low), Codex: No data020406080Claude Sonnet 5.5 (xhigh)Claude Code80Claude Opus 5.5 (xhigh)Claude Code79Claude Opus 5 (high)Claude Code79Claude Opus 5.5 (medium)Claude Code79Claude Opus 5.5 (high)Claude Code78Claude Opus 4.7 (high)Claude Code77Claude Sonnet 5.5 (high)Claude Code77Claude Sonnet 5.5 (medium)Claude Code76Claude Haiku 5.5 (xhigh)Claude Code76Claude Opus 4.8 (high)Claude Code75Claude Haiku 5.5 (high)Claude Code74Claude Sonnet 5 (high)Claude Code73Claude Haiku 5.5 (medium)Claude Code73Claude Haiku 4.5 (Reasoning)Claude Code70
How to read this chart

What this metric means. The share of tasks the entry passed, 0 to 100.

Data table: MultiGlobeQA score
MultiGlobeQA score
ModelDeveloperMultiGlobeQA score
Claude Sonnet 5.5 (xhigh), Claude CodeAnthropic80
Claude Opus 5.5 (xhigh), Claude CodeAnthropic79
Claude Opus 5 (high), Claude CodeAnthropic79
Claude Opus 5.5 (medium), Claude CodeAnthropic79
Claude Opus 5.5 (high), Claude CodeAnthropic78
Claude Opus 4.7 (high), Claude CodeAnthropic77
Claude Sonnet 5.5 (high), Claude CodeAnthropic77
Claude Sonnet 5.5 (medium), Claude CodeAnthropic76
Claude Haiku 5.5 (xhigh), Claude CodeAnthropic76
Claude Opus 4.8 (high), Claude CodeAnthropic75
Claude Haiku 5.5 (high), Claude CodeAnthropic74
Claude Sonnet 5 (high), Claude CodeAnthropic73
Claude Haiku 5.5 (medium), Claude CodeAnthropic73
Claude Haiku 4.5 (Reasoning), Claude CodeAnthropic70
Claude Sonnet 4.6 (high), Terminus-2AnthropicNo data
DeepSeek V4 Flash (max), Terminus-2DeepSeekNo data
DeepSeek V4 Flash (high), Terminus-2DeepSeekNo data
DeepSeek V4 Pro (max), Terminus-2DeepSeekNo data
DeepSeek V4 Pro (high), Terminus-2DeepSeekNo data
Gemini 3.1 Flash-Lite (low), Terminus-2GoogleNo data
Gemini 3.1 Flash-Lite (minimal), Terminus-2GoogleNo data
Gemini 3.1 Flash-Lite (high), Terminus-2GoogleNo data
Gemini 3.1 Pro (preview) (low), Terminus-2GoogleNo data
Gemini 3.1 Pro (preview) (high), Terminus-2GoogleNo data
Gemini 3.8 Flash (high), Terminus-2GoogleNo data
Gemini 3.8 Flash (low), Terminus-2GoogleNo data
Gemma 4 26B A4B (Reasoning), Terminus-2GoogleNo data
GLM-4.7-Flash (Reasoning), Terminus-2Z.aiNo data
GLM-5.2 (high), Terminus-2Z.aiNo data
GLM-5.2 (Non-reasoning), Terminus-2Z.aiNo data
GLM-5.2 (max), Terminus-2Z.aiNo data
GLM-5.3-Flash (low), Terminus-2Z.aiNo data
GLM-5.3-Flash (max), Terminus-2Z.aiNo data
GLM-5.3 (low), Terminus-2Z.aiNo data
GLM-5.3 (max), Terminus-2Z.aiNo data
gpt-oss-120b (low), Terminus-2OpenAINo data
gpt-oss-120b (high), Terminus-2OpenAINo data
gpt-oss-20b (high), Terminus-2OpenAINo data
Kimi K2.6 (Reasoning), Terminus-2Moonshot AINo data
Kimi K2.7 Code (Reasoning), Terminus-2Moonshot AINo data
Kimi K3 (Reasoning), Terminus-2Moonshot AINo data
Llama 3.3 70B (Non-reasoning), Terminus-2MetaNo data
MiniMax M3.1 Flash (max), Terminus-2OtherNo data
Mistral Large 3 (Non-reasoning), Terminus-2Mistral AINo data
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2NVIDIANo data
Nemotron 3 Ultra (high), Terminus-2NVIDIANo data
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2NVIDIANo data
Qwen 3.8 27B (xhigh), Terminus-2Alibaba (Qwen)No data
GLM-4.7-Flash (Reasoning), Claude CodeZ.aiNo data
GLM-5.2 (max), Claude CodeZ.aiNo data
GLM-5.3-Flash (max), Claude CodeZ.aiNo data
GLM-5.3 (max), Claude CodeZ.aiNo data
DeepSeek V4 Flash (high), CodexDeepSeekNo data
DeepSeek V4 Pro (high), CodexDeepSeekNo data
DeepSeek V4.1 Flash (max), CodexOtherNo data
gpt-oss-120b (high), CodexOpenAINo data
gpt-oss-20b (high), CodexOpenAINo data
Kimi K2.6 (Reasoning), Kimi CodeMoonshot AINo data
Kimi K2.7 Code (Reasoning), Kimi CodeMoonshot AINo data
Qwen 3.8 27B (xhigh), Qwen CodeAlibaba (Qwen)No data
GPT-6.1 Sol (medium), CodexOpenAINo data
GPT-6.1 Sol (high), CodexOpenAINo data
GPT-6.1 Sol (xhigh), CodexOpenAINo data
GPT-6 Luna (xhigh), CodexOpenAINo data
GPT-6 Sol (medium), CodexOpenAINo data
GPT-6 Sol (high), CodexOpenAINo data
GPT-6 Luna (medium), CodexOpenAINo data
GPT-6 Luna (high), CodexOpenAINo data
GPT-5.6 Sol (medium), CodexOpenAINo data
GPT-5.6 Sol (high), CodexOpenAINo data
GPT-5.6 Terra (high), CodexOpenAINo data
GPT-5.6 Luna (medium), CodexOpenAINo data
GPT-5.6 Luna (high), CodexOpenAINo data
GPT-5.6 Luna (xhigh), CodexOpenAINo data
GPT-6 Luna (low), CodexOpenAINo data
GPT-5.6 Luna (low), CodexOpenAINo data

MultiGlobeQA: score vs. cost per task

MultiGlobeQA score against average cost per task (USD) · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
MultiGlobeQA: score vs. cost per taskMultiGlobeQA score (0 to 100) against cost per task in US dollars, log scale: Claude Haiku 4.5 (Reasoning), Claude Code: 70.41, $0.067; Claude Opus 5.5 (medium), Claude Code: 78.57, $0.074; Claude Opus 5.5 (high), Claude Code: 78.23, $0.081; Claude Sonnet 5.5 (medium), Claude Code: 75.51, $0.035; Claude Sonnet 5.5 (high), Claude Code: 76.53, $0.040; Claude Haiku 5.5 (medium), Claude Code: 72.79, $0.0037; Claude Haiku 5.5 (high), Claude Code: 74.49, $0.0043; Claude Opus 5.5 (xhigh), Claude Code: 78.91, $0.097; Claude Sonnet 5.5 (xhigh), Claude Code: 79.59, $0.049; Claude Haiku 5.5 (xhigh), Claude Code: 75.51, $0.0057; Claude Opus 5 (high), Claude Code: 78.91, $0.16; Claude Sonnet 5 (high), Claude Code: 73.47, $0.12; Claude Opus 4.8 (high), Claude Code: 75.17, $0.17; Claude Opus 4.7 (high), Claude Code: 76.87, $0.23Most attractive quadrant6870727476788082$0.002$0.005$0.01$0.02$0.05$0.10$0.20$0.50Cost per task (USD, log scale)MultiGlobeQA scoreClaude Sonnet 5.5 (xhigh), 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 Opus 5.5 (xhigh), Claude CodeClaude Opus 5 (high), Claude CodeClaude Opus 5.5 (medium), Claude CodeClaude Opus 5.5 (high), Claude CodeClaude Opus 4.7 (high), Claude CodeClaude Sonnet 5.5 (medium), Claude CodeClaude Opus 4.8 (high), Claude CodeClaude Sonnet 5 (high), Claude CodeClaude Haiku 4.5 (Reasoning), Claude Code
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 task (log scale); higher means a higher MultiGlobeQA 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: MultiGlobeQA: score vs. cost per task

Token usage

MultiGlobeQA: tokens per task

Average tokens per task by type · Lower is better

  • Uncached input
  • Cached input
  • Output (reasoning included)
MultiGlobeQA: tokens per taskClaude Sonnet 5.5 (medium), Claude Code: 62k; Claude Opus 5.5 (medium), Claude Code: 62k; Claude Opus 5.5 (high), Claude Code: 65k; Claude Sonnet 5.5 (high), Claude Code: 67k; Claude Opus 5.5 (xhigh), Claude Code: 73k; Claude Sonnet 5.5 (xhigh), Claude Code: 74k; Claude Opus 5 (high), Claude Code: 90k; Claude Opus 4.8 (high), Claude Code: 91k; Claude Haiku 5.5 (medium), Claude Code: 133k; Claude Haiku 5.5 (high), Claude Code: 141k; Claude Opus 4.7 (high), Claude Code: 163k; Claude Haiku 5.5 (xhigh), Claude Code: 170k; Claude Sonnet 5 (high), Claude Code: 194k; Claude Haiku 4.5 (Reasoning), Claude Code: 229k0100k200k300k400kClaude Sonnet 5.5 (medium)Claude Code62kClaude Opus 5.5 (medium)Claude Code62kClaude Opus 5.5 (high)Claude Code65kClaude Sonnet 5.5 (high)Claude Code67kClaude Opus 5.5 (xhigh)Claude Code73kClaude Sonnet 5.5 (xhigh)Claude Code74kClaude Opus 5 (high)Claude Code90kClaude Opus 4.8 (high)Claude Code91kClaude Haiku 5.5 (medium)Claude Code133kClaude Haiku 5.5 (high)Claude Code141kClaude Opus 4.7 (high)Claude Code163kClaude Haiku 5.5 (xhigh)Claude Code170kClaude Sonnet 5 (high)Claude Code194kClaude Haiku 4.5 (Reasoning)Claude Code229k
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: MultiGlobeQA: tokens per task
MultiGlobeQA: tokens per task
ModelDeveloperUncached inputCached inputOutput (reasoning included)Total
Claude Sonnet 5.5 (medium), Claude CodeAnthropic5k56k71762k
Claude Opus 5.5 (medium), Claude CodeAnthropic6k56k83562k
Claude Opus 5.5 (high), Claude CodeAnthropic6k58k95465k
Claude Sonnet 5.5 (high), Claude CodeAnthropic6k59k88067k
Claude Opus 5.5 (xhigh), Claude CodeAnthropic7k65k2k73k
Claude Sonnet 5.5 (xhigh), Claude CodeAnthropic7k65k1k74k
Claude Opus 5 (high), Claude CodeAnthropic7k81k2k90k
Claude Opus 4.8 (high), Claude CodeAnthropic9k80k2k91k
Claude Haiku 5.5 (medium), Claude CodeAnthropic9k122k1k133k
Claude Haiku 5.5 (high), Claude CodeAnthropic9k129k2k141k
Claude Opus 4.7 (high), Claude CodeAnthropic10k151k2k163k
Claude Haiku 5.5 (xhigh), Claude CodeAnthropic11k155k4k170k
Claude Sonnet 5 (high), Claude CodeAnthropic11k179k3k194k
Claude Haiku 4.5 (Reasoning), Claude CodeAnthropic13k212k4k229k

Cost

MultiGlobeQA: cost per task

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

  • Uncached input
  • Cached input
  • Output
  • Not split by token type
MultiGlobeQA: cost per taskValues in US dollars: Claude Haiku 5.5 (medium), Claude Code: $0.0037; Claude Haiku 5.5 (high), Claude Code: $0.0043; Claude Haiku 5.5 (xhigh), Claude Code: $0.0057; Claude Sonnet 5.5 (medium), Claude Code: $0.035; Claude Sonnet 5.5 (high), Claude Code: $0.040; Claude Sonnet 5.5 (xhigh), Claude Code: $0.049; Claude Haiku 4.5 (Reasoning), Claude Code: $0.067; Claude Opus 5.5 (medium), Claude Code: $0.074; Claude Opus 5.5 (high), Claude Code: $0.081; Claude Opus 5.5 (xhigh), Claude Code: $0.097; Claude Sonnet 5 (high), Claude Code: $0.12; Claude Opus 5 (high), Claude Code: $0.16; Claude Opus 4.8 (high), Claude Code: $0.17; Claude Opus 4.7 (high), Claude Code: $0.23$0$0.10$0.20$0.30$0.40Claude Haiku 5.5 (medium)Claude Code$0.0037Claude Haiku 5.5 (high)Claude Code$0.0043Claude Haiku 5.5 (xhigh)Claude Code$0.0057Claude Sonnet 5.5 (medium)Claude Code$0.035Claude Sonnet 5.5 (high)Claude Code$0.040Claude Sonnet 5.5 (xhigh)Claude Code$0.049Claude Haiku 4.5 (Reasoning)Claude Code$0.067Claude Opus 5.5 (medium)Claude Code$0.074Claude Opus 5.5 (high)Claude Code$0.081Claude Opus 5.5 (xhigh)Claude Code$0.097Claude Sonnet 5 (high)Claude Code$0.12Claude Opus 5 (high)Claude Code$0.16Claude Opus 4.8 (high)Claude Code$0.17Claude Opus 4.7 (high)Claude Code$0.23
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: MultiGlobeQA: cost per task
MultiGlobeQA: cost per task
ModelDeveloperUncached inputCached inputOutputNot split by token typeTotal
Claude Haiku 5.5 (medium), Claude CodeAnthropic$0.00088$0.0012$0.00075$0.00088$0.0037
Claude Haiku 5.5 (high), Claude CodeAnthropic$0.00093$0.0013$0.0011$0.00093$0.0043
Claude Haiku 5.5 (xhigh), Claude CodeAnthropic$0.0011$0.0016$0.0020$0.0011$0.0057
Claude Sonnet 5.5 (medium), Claude CodeAnthropic$0.011$0.0056$0.0072$0.011$0.035
Claude Sonnet 5.5 (high), Claude CodeAnthropic$0.013$0.0059$0.0088$0.013$0.040
Claude Sonnet 5.5 (xhigh), Claude CodeAnthropic$0.014$0.0065$0.013$0.014$0.049
Claude Haiku 4.5 (Reasoning), Claude CodeAnthropic$0.013$0.021$0.019$0.013$0.067
Claude Opus 5.5 (medium), Claude CodeAnthropic$0.023$0.011$0.017$0.023$0.074
Claude Opus 5.5 (high), Claude CodeAnthropic$0.025$0.012$0.019$0.025$0.081
Claude Opus 5.5 (xhigh), Claude CodeAnthropic$0.026$0.013$0.032$0.026$0.097
Claude Sonnet 5 (high), Claude CodeAnthropic$0.022$0.036$0.035$0.022$0.12
Claude Opus 5 (high), Claude CodeAnthropic$0.037$0.040$0.050$0.037$0.16
Claude Opus 4.8 (high), Claude CodeAnthropic$0.043$0.040$0.048$0.043$0.17
Claude Opus 4.7 (high), Claude CodeAnthropic$0.049$0.076$0.060$0.049$0.23

Speed

MultiGlobeQA: time per task

Time per task (at 100 output tokens/s), minutes · Lower is better

MultiGlobeQA: time per taskMultiGlobeQA: time per task: Claude Sonnet 5.5 (medium), Claude Code: 0.2 min; Claude Opus 5.5 (medium), Claude Code: 0.2 min; Claude Sonnet 5.5 (high), Claude Code: 0.2 min; Claude Opus 5.5 (high), Claude Code: 0.2 min; Claude Sonnet 5.5 (xhigh), Claude Code: 0.3 min; Claude Haiku 5.5 (medium), Claude Code: 0.3 min; Claude Opus 5.5 (xhigh), Claude Code: 0.4 min; Claude Opus 4.8 (high), Claude Code: 0.4 min; Claude Opus 5 (high), Claude Code: 0.4 min; Claude Haiku 5.5 (high), Claude Code: 0.5 min; Claude Opus 4.7 (high), Claude Code: 0.5 min; Claude Sonnet 5 (high), Claude Code: 0.7 min; Claude Haiku 5.5 (xhigh), Claude Code: 0.8 min; Claude Haiku 4.5 (Reasoning), Claude Code: 0.8 min; Claude Sonnet 4.6 (high), Terminus-2: No data; DeepSeek V4 Flash (max), Terminus-2: No data; DeepSeek V4 Flash (high), Terminus-2: No data; DeepSeek V4 Pro (max), Terminus-2: No data; DeepSeek V4 Pro (high), Terminus-2: No data; Gemini 3.1 Flash-Lite (low), Terminus-2: No data; Gemini 3.1 Flash-Lite (minimal), Terminus-2: No data; Gemini 3.1 Flash-Lite (high), Terminus-2: No data; Gemini 3.1 Pro (preview) (low), Terminus-2: No data; Gemini 3.1 Pro (preview) (high), Terminus-2: No data; Gemini 3.8 Flash (high), Terminus-2: No data; Gemini 3.8 Flash (low), Terminus-2: No data; Gemma 4 26B A4B (Reasoning), Terminus-2: No data; GLM-4.7-Flash (Reasoning), Terminus-2: No data; GLM-5.2 (high), Terminus-2: No data; GLM-5.2 (Non-reasoning), Terminus-2: No data; GLM-5.2 (max), Terminus-2: No data; GLM-5.3-Flash (low), Terminus-2: No data; GLM-5.3-Flash (max), Terminus-2: No data; GLM-5.3 (low), Terminus-2: No data; GLM-5.3 (max), Terminus-2: No data; gpt-oss-120b (low), Terminus-2: No data; gpt-oss-120b (high), Terminus-2: No data; gpt-oss-20b (high), Terminus-2: No data; Kimi K2.6 (Reasoning), Terminus-2: No data; Kimi K2.7 Code (Reasoning), Terminus-2: No data; Kimi K3 (Reasoning), Terminus-2: No data; Llama 3.3 70B (Non-reasoning), Terminus-2: No data; MiniMax M3.1 Flash (max), Terminus-2: No data; Mistral Large 3 (Non-reasoning), Terminus-2: No data; Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2: No data; Nemotron 3 Ultra (high), Terminus-2: No data; Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2: No data; Qwen 3.8 27B (xhigh), Terminus-2: No data; GLM-4.7-Flash (Reasoning), Claude Code: No data; GLM-5.2 (max), Claude Code: No data; GLM-5.3-Flash (max), Claude Code: No data; GLM-5.3 (max), Claude Code: No data; DeepSeek V4 Flash (high), Codex: No data; DeepSeek V4 Pro (high), Codex: No data; DeepSeek V4.1 Flash (max), Codex: No data; gpt-oss-120b (high), Codex: No data; gpt-oss-20b (high), Codex: No data; Kimi K2.6 (Reasoning), Kimi Code: No data; Kimi K2.7 Code (Reasoning), Kimi Code: No data; Qwen 3.8 27B (xhigh), Qwen Code: No data; GPT-6.1 Sol (medium), Codex: No data; GPT-6.1 Sol (high), Codex: No data; GPT-6.1 Sol (xhigh), Codex: No data; GPT-6 Luna (xhigh), Codex: No data; GPT-6 Sol (medium), Codex: No data; GPT-6 Sol (high), Codex: No data; GPT-6 Luna (medium), Codex: No data; GPT-6 Luna (high), Codex: No data; GPT-5.6 Sol (medium), Codex: No data; GPT-5.6 Sol (high), Codex: No data; GPT-5.6 Terra (high), Codex: No data; GPT-5.6 Luna (medium), Codex: No data; GPT-5.6 Luna (high), Codex: No data; GPT-5.6 Luna (xhigh), Codex: No data; GPT-6 Luna (low), Codex: No data; GPT-5.6 Luna (low), Codex: No data0 min0.2 min0.4 min0.6 min0.8 minClaude Sonnet 5.5 (medium)Claude Code0.2 minClaude Opus 5.5 (medium)Claude Code0.2 minClaude Sonnet 5.5 (high)Claude Code0.2 minClaude Opus 5.5 (high)Claude Code0.2 minClaude Sonnet 5.5 (xhigh)Claude Code0.3 minClaude Haiku 5.5 (medium)Claude Code0.3 minClaude Opus 5.5 (xhigh)Claude Code0.4 minClaude Opus 4.8 (high)Claude Code0.4 minClaude Opus 5 (high)Claude Code0.4 minClaude Haiku 5.5 (high)Claude Code0.5 minClaude Opus 4.7 (high)Claude Code0.5 minClaude Sonnet 5 (high)Claude Code0.7 minClaude Haiku 5.5 (xhigh)Claude Code0.8 minClaude Haiku 4.5 (Reasoning)Claude Code0.8 min
How to read this chart

Time per task. 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: MultiGlobeQA: time per task
MultiGlobeQA: time per task
ModelDeveloperTime per task (min)
Claude Sonnet 5.5 (medium), Claude CodeAnthropic0.2 min
Claude Opus 5.5 (medium), Claude CodeAnthropic0.2 min
Claude Sonnet 5.5 (high), Claude CodeAnthropic0.2 min
Claude Opus 5.5 (high), Claude CodeAnthropic0.2 min
Claude Sonnet 5.5 (xhigh), Claude CodeAnthropic0.3 min
Claude Haiku 5.5 (medium), Claude CodeAnthropic0.3 min
Claude Opus 5.5 (xhigh), Claude CodeAnthropic0.4 min
Claude Opus 4.8 (high), Claude CodeAnthropic0.4 min
Claude Opus 5 (high), Claude CodeAnthropic0.4 min
Claude Haiku 5.5 (high), Claude CodeAnthropic0.5 min
Claude Opus 4.7 (high), Claude CodeAnthropic0.5 min
Claude Sonnet 5 (high), Claude CodeAnthropic0.7 min
Claude Haiku 5.5 (xhigh), Claude CodeAnthropic0.8 min
Claude Haiku 4.5 (Reasoning), Claude CodeAnthropic0.8 min
Claude Sonnet 4.6 (high), Terminus-2AnthropicNo data
DeepSeek V4 Flash (max), Terminus-2DeepSeekNo data
DeepSeek V4 Flash (high), Terminus-2DeepSeekNo data
DeepSeek V4 Pro (max), Terminus-2DeepSeekNo data
DeepSeek V4 Pro (high), Terminus-2DeepSeekNo data
Gemini 3.1 Flash-Lite (low), Terminus-2GoogleNo data
Gemini 3.1 Flash-Lite (minimal), Terminus-2GoogleNo data
Gemini 3.1 Flash-Lite (high), Terminus-2GoogleNo data
Gemini 3.1 Pro (preview) (low), Terminus-2GoogleNo data
Gemini 3.1 Pro (preview) (high), Terminus-2GoogleNo data
Gemini 3.8 Flash (high), Terminus-2GoogleNo data
Gemini 3.8 Flash (low), Terminus-2GoogleNo data
Gemma 4 26B A4B (Reasoning), Terminus-2GoogleNo data
GLM-4.7-Flash (Reasoning), Terminus-2Z.aiNo data
GLM-5.2 (high), Terminus-2Z.aiNo data
GLM-5.2 (Non-reasoning), Terminus-2Z.aiNo data
GLM-5.2 (max), Terminus-2Z.aiNo data
GLM-5.3-Flash (low), Terminus-2Z.aiNo data
GLM-5.3-Flash (max), Terminus-2Z.aiNo data
GLM-5.3 (low), Terminus-2Z.aiNo data
GLM-5.3 (max), Terminus-2Z.aiNo data
gpt-oss-120b (low), Terminus-2OpenAINo data
gpt-oss-120b (high), Terminus-2OpenAINo data
gpt-oss-20b (high), Terminus-2OpenAINo data
Kimi K2.6 (Reasoning), Terminus-2Moonshot AINo data
Kimi K2.7 Code (Reasoning), Terminus-2Moonshot AINo data
Kimi K3 (Reasoning), Terminus-2Moonshot AINo data
Llama 3.3 70B (Non-reasoning), Terminus-2MetaNo data
MiniMax M3.1 Flash (max), Terminus-2OtherNo data
Mistral Large 3 (Non-reasoning), Terminus-2Mistral AINo data
Nemotron 3 Nano Omni 30B (Reasoning), Terminus-2NVIDIANo data
Nemotron 3 Ultra (high), Terminus-2NVIDIANo data
Nemotron 3.5 Super VL 120B (Reasoning), Terminus-2NVIDIANo data
Qwen 3.8 27B (xhigh), Terminus-2Alibaba (Qwen)No data
GLM-4.7-Flash (Reasoning), Claude CodeZ.aiNo data
GLM-5.2 (max), Claude CodeZ.aiNo data
GLM-5.3-Flash (max), Claude CodeZ.aiNo data
GLM-5.3 (max), Claude CodeZ.aiNo data
DeepSeek V4 Flash (high), CodexDeepSeekNo data
DeepSeek V4 Pro (high), CodexDeepSeekNo data
DeepSeek V4.1 Flash (max), CodexOtherNo data
gpt-oss-120b (high), CodexOpenAINo data
gpt-oss-20b (high), CodexOpenAINo data
Kimi K2.6 (Reasoning), Kimi CodeMoonshot AINo data
Kimi K2.7 Code (Reasoning), Kimi CodeMoonshot AINo data
Qwen 3.8 27B (xhigh), Qwen CodeAlibaba (Qwen)No data
GPT-6.1 Sol (medium), CodexOpenAINo data
GPT-6.1 Sol (high), CodexOpenAINo data
GPT-6.1 Sol (xhigh), CodexOpenAINo data
GPT-6 Luna (xhigh), CodexOpenAINo data
GPT-6 Sol (medium), CodexOpenAINo data
GPT-6 Sol (high), CodexOpenAINo data
GPT-6 Luna (medium), CodexOpenAINo data
GPT-6 Luna (high), CodexOpenAINo data
GPT-5.6 Sol (medium), CodexOpenAINo data
GPT-5.6 Sol (high), CodexOpenAINo data
GPT-5.6 Terra (high), CodexOpenAINo data
GPT-5.6 Luna (medium), CodexOpenAINo data
GPT-5.6 Luna (high), CodexOpenAINo data
GPT-5.6 Luna (xhigh), CodexOpenAINo data
GPT-6 Luna (low), CodexOpenAINo data
GPT-5.6 Luna (low), CodexOpenAINo data

MultiGlobeQA: score vs. time per task

MultiGlobeQA score against time per task (at 100 output tokens/s), minutes · Higher and further left is better

  • Most attractive quadrant
  • Pareto line
MultiGlobeQA: score vs. time per taskMultiGlobeQA score (0 to 100) against time per task (minutes), log scale: Claude Haiku 4.5 (Reasoning), Claude Code: 70.41, 0.8 min; Claude Opus 5.5 (medium), Claude Code: 78.57, 0.2 min; Claude Opus 5.5 (high), Claude Code: 78.23, 0.2 min; Claude Sonnet 5.5 (medium), Claude Code: 75.51, 0.2 min; Claude Sonnet 5.5 (high), Claude Code: 76.53, 0.2 min; Claude Haiku 5.5 (medium), Claude Code: 72.79, 0.3 min; Claude Haiku 5.5 (high), Claude Code: 74.49, 0.5 min; Claude Opus 5.5 (xhigh), Claude Code: 78.91, 0.4 min; Claude Sonnet 5.5 (xhigh), Claude Code: 79.59, 0.3 min; Claude Haiku 5.5 (xhigh), Claude Code: 75.51, 0.8 min; Claude Opus 5 (high), Claude Code: 78.91, 0.4 min; Claude Sonnet 5 (high), Claude Code: 73.47, 0.7 min; Claude Opus 4.8 (high), Claude Code: 75.17, 0.4 min; Claude Opus 4.7 (high), Claude Code: 76.87, 0.5 minMost attractive quadrant68707274767880820.1 min0.2 min0.5 min1 minTime per task (minutes, log scale)MultiGlobeQA scoreClaude Sonnet 5.5 (xhigh), Claude CodeClaude Opus 5.5 (medium), Claude CodeClaude Opus 5.5 (high), Claude CodeClaude Sonnet 5.5 (high), Claude CodeClaude Sonnet 5.5 (medium), Claude CodeClaude Opus 5.5 (xhigh), Claude CodeClaude Opus 5 (high), Claude CodeClaude Opus 4.7 (high), Claude CodeClaude Haiku 5.5 (xhigh), Claude CodeClaude Opus 4.8 (high), Claude CodeClaude Haiku 5.5 (high), Claude CodeClaude Sonnet 5 (high), Claude CodeClaude Haiku 5.5 (medium), Claude CodeClaude Haiku 4.5 (Reasoning), Claude Code
How to read this chart

Time per task. 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 MultiGlobeQA 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: MultiGlobeQA: score vs. time per task

Score vs. release date

MultiGlobeQA: score vs. release date

MultiGlobeQA score against the model's public release date

MultiGlobeQA: score vs. release dateMultiGlobeQA score (0 to 100) against release date: Claude Haiku 4.5 (Reasoning), Claude Code: 70.41, 15 October 2025; Claude Opus 5.5 (medium), Claude Code: 78.57, 22 September 2026; Claude Opus 5.5 (high), Claude Code: 78.23, 22 September 2026; Claude Sonnet 5.5 (medium), Claude Code: 75.51, 28 September 2026; Claude Sonnet 5.5 (high), Claude Code: 76.53, 28 September 2026; Claude Haiku 5.5 (medium), Claude Code: 72.79, 7 October 2026; Claude Haiku 5.5 (high), Claude Code: 74.49, 7 October 2026; Claude Opus 5.5 (xhigh), Claude Code: 78.91, 22 September 2026; Claude Sonnet 5.5 (xhigh), Claude Code: 79.59, 28 September 2026; Claude Haiku 5.5 (xhigh), Claude Code: 75.51, 7 October 2026; Claude Opus 5 (high), Claude Code: 78.91, 24 July 2026; Claude Sonnet 5 (high), Claude Code: 73.47, 30 June 2026; Claude Opus 4.8 (high), Claude Code: 75.17, 28 May 2026; Claude Opus 4.7 (high), Claude Code: 76.87, 16 April 20266870727476788082Oct 2025Jan 2026Apr 2026Jul 2026Oct 2026Jan 2027Release dateMultiGlobeQA scoreClaude Sonnet 5.5 (xhigh), Claude CodeClaude Opus 5.5 (xhigh), Claude CodeClaude Opus 5 (high), Claude CodeClaude Opus 5.5 (medium), Claude CodeClaude Opus 5.5 (high), Claude CodeClaude Opus 4.7 (high), Claude CodeClaude Sonnet 5.5 (high), Claude CodeClaude Sonnet 5.5 (medium), Claude CodeClaude Haiku 5.5 (xhigh), Claude CodeClaude Opus 4.8 (high), Claude CodeClaude Haiku 5.5 (high), Claude CodeClaude Sonnet 5 (high), Claude CodeClaude Haiku 5.5 (medium), Claude CodeClaude Haiku 4.5 (Reasoning), Claude Code
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 MultiGlobeQA score. Models with no published release date are not plotted.

Data table: MultiGlobeQA: score vs. release date

Background

MultiGlobeQA asks spatial questions about places all over the world: what lies within, next to or nearest to what, how far apart things are, and how many there are. Its answers were computed by spatial queries over three knowledge graphs built from OpenStreetMap and KnowWhereGraph.

Licence: data Open Database License 1.0 (© OpenStreetMap contributors); KnowWhereGraph facts CC BY 4.0; code MIT.

Published by Böckling, Nosova, Paulheim and Iana.

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