Measurement Data Bank
A curated data bank of AI evaluation results, standardized for measurement.
The data layer
measurement-db standardizes evaluation results from 309 public benchmarks into (model × item) response matrices, the raw observations that item response theory and other psychometric models are estimated from. It is the data layer beneath torch_measure.
Maintained by Nhi Truong, Sang Truong, and Sanmi Koyejo
309
Benchmarks curated
2.9M
Unique evaluation items
64.8M
Model–item responses
01What it is
Coverage spans reasoning, coding, agentic, multimodal, safety, and human-preference benchmarks. Every benchmark ships a reproducible build script, and each response carries its model, item, benchmark, and test condition.
02Coverage
What the bank measures, and how deeply: the frontier models it tracks, and the domains its benchmarks cover.
Ranked by items asked
Frontier Model Coverage
A curated set of frontier models ranked by the number of distinct benchmark items they have been evaluated on.
- 1
Microsoft
Phi-4
45,415 - 2
Meta
Llama 4 Maverick
37,096 - 3
Salesforce
xGen-MM
7,541 - 4
Tencent
Hunyuan Standard Vision
7,433 - 5
Cohere
Command A
7,000 - 6
Google
Gemini 3.1 Pro
3,422 - 7
IBM
Granite 4.0 Micro
2,944 - 8
OpenAI
GPT-5.5
2,276 - 9
Mistral
Large 3
2,070 - 10
DeepSeek
V4 Pro
1,800 - 11
Anthropic
Claude Opus 4.8
902 - 12
Alibaba
Qwen3.7 Max
41 - 13
Amazon
Nova 2 Lite
40 - 14M
Moonshot
Kimi K2.7
40 - 15
xAI
Grok 4.3
40
Ranked by items covered
Domain Coverage Assessment
Benchmarks that span multiple domains count toward each, so the totals overlap rather than partition the bank.
- 1
General
86 benchmarks
1,904,472 - 2
Reasoning
98 benchmarks
1,009,149 - 3
Safety
60 benchmarks
567,383 - 4
Mathematics
37 benchmarks
347,746 - 5
ML Engineering
8 benchmarks
272,021 - 6
Preference
13 benchmarks
206,454 - 7
Science
30 benchmarks
180,260 - 8
Medicine
38 benchmarks
151,652 - 9
Knowledge
15 benchmarks
110,608 - 10
Law
4 benchmarks
87,020 - 11
Software Engineering
39 benchmarks
75,135 - 12
Multilingual
10 benchmarks
69,407 - 13
Cultural
3 benchmarks
32,067 - 14
NLP Tasks
4 benchmarks
19,905 - 15
Cybersecurity
10 benchmarks
17,031
Average score per domain, every model
Model × Domain Scores
Every model’s average score across each benchmark domain. A hatched cell means the model was never measured in that domain.
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