Model Evaluation
128 AI Wiki articles on Model Evaluation. The most referenced are Benchmark (AI), Overfitting and Interpretability.
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AGIEval
AGIEval is an AI benchmark for evaluating foundation models on tasks that were originally designed for, and taken by, humans. Rather than building synthetic...
AI Benchmarks
ARC Evals
ARC Evals was the evaluations team incubated inside the Alignment Research Center (ARC) between 2022 and 2023, and the direct predecessor of METR (Model...
AI SafetyResearch Organizations
ARC-AGI-2
ARC-AGI-2 (Abstraction and Reasoning Corpus for Artificial General Intelligence 2) is an abstract reasoning benchmark for artificial intelligence, released on...
2025 in artificial intelligenceAI Benchmarks
AUC (Area Under the ROC Curve)
AUC (Area Under the ROC Curve) is a classifier evaluation metric equal to the probability that a model ranks a randomly chosen positive instance higher than a...
Machine Learning
AUC-ROC
See also: Machine learning terms AUC (Area Under the Curve), most often the area under the ROC curve (AUC-ROC), is a threshold-independent evaluation metric...
Machine LearningStatistics
Accuracy
See also: machine learning terms, confusion matrix, precision, recall, F1 score Accuracy is a classification metric that measures the fraction of predictions a...
Machine Learning
Agent evaluation
Agent evaluation is the systematic measurement of how well AI agents (LLM-based systems that plan and act over multiple steps using tools) perform on...
AI AgentsAI Benchmarks
Algorithmic bias
Algorithmic bias is the tendency of a computer system to produce systematic, repeatable errors that advantage some groups of people over others. The term...
AI EthicsAI Policy & Regulation
Area under the curve
Area under the curve (AUC) is a single scalar metric that summarizes the performance of a binary classifier or diagnostic test across all possible decision...
Machine LearningStatistics
Arena-Hard
Arena-Hard (and its evaluation tool Arena-Hard-Auto) is an automatic large language model (LLM) benchmark developed by the team behind Chatbot Arena that...
AI Benchmarks
Arize Phoenix
Arize Phoenix is an open-source AI observability and evaluation platform developed by Arize AI for tracing, evaluating, and debugging large language model...
AI CompaniesDeveloper Tools
Average Precision
See also: precision, recall, F1 score, confusion matrix, AUC, precision-recall curve Average precision (AP) is an evaluation metric that summarizes the...
Computer VisionInformation Retrieval
BABILong
BABILong is a benchmark for testing how well a large language model can reason over facts scattered through very long text. It was introduced by Yuri Kuratov,...
AI BenchmarksLarge Language Models
BERTScore
BERTScore is an automatic, reference-based metric for evaluating text generation that scores a candidate sentence against one or more references by comparing...
Machine LearningNatural Language Processing
BLEU (Bilingual Evaluation Understudy)
BLEU (Bilingual Evaluation Understudy) is an automatic evaluation metric that scores the quality of machine translation output by measuring how many word...
Machine LearningNatural Language Processing
Baseline
See also: Machine learning terms, Model evaluation In machine learning, a baseline is a simple reference model or method used as a point of comparison to judge...
Machine Learning
Benchmark (AI)
In artificial intelligence and machine learning, a benchmark is a specified evaluation used to compare systems under common conditions. A benchmark normally...
AI Benchmarks
Best AI Models for Reasoning and Math
As of July 2026, the strongest general reasoning models are Anthropic's Claude Opus 4.8 and Claude Fable 5, OpenAI's GPT-5.5, and Google's Gemini 3.1 Pro and...
Large Language ModelsReasoning Models
CIDEr
CIDEr (Consensus-based Image Description Evaluation) is an automatic evaluation metric for image captioning that scores a machine-generated caption by how...
Computer VisionMachine Learning
Calibration Layer
A calibration layer is a post-prediction adjustment appended to a trained machine learning model that rescales its raw output scores or predicted probabilities...
Deep LearningMachine Learning
ChemBench
ChemBench is an automated AI benchmark that measures the chemical knowledge, reasoning, and safety judgment of large language models and compares their...
AI Benchmarks
Classification Threshold
A classification threshold (also called a decision threshold or cut-off point) is a numeric value used to convert the continuous probability output of a...
Machine Learning
ClusterMAX
ClusterMAX is a rating and ranking system for GPU cloud providers published by the research firm SemiAnalysis. It scores providers against ten criteria and...
AI InfrastructureData Centers
Confusion Matrix
A confusion matrix is a table that summarizes the performance of a classification model by tabulating its predicted class labels against the actual class...
Machine Learning
Coreference Resolution
Coreference resolution is the natural language processing task of finding all the expressions in a text that refer to the same entity and grouping them...
AI BenchmarksMachine Learning
Cross-Validation
Cross-validation is a statistical resampling technique used in machine learning to estimate how accurately a predictive model will generalize to data it was...
Machine Learning
Cybench
Cybench (short for Cybersecurity benchmark) is an open-source evaluation framework for measuring the cybersecurity capabilities and risks of large language...
AI BenchmarksAI Safety
Data contamination
Data contamination is the presence of benchmark evaluation data in the corpus used to train a model, so that reported scores partly measure recall of material...
AI BenchmarksData & Datasets
Decision Threshold
A decision threshold (also called a classification threshold or cutoff point) is a value used to convert the continuous probability output of a machine...
Machine Learning
Distribution shift
Distribution shift is the condition in which the probability distribution that produced a model's training data differs from the distribution that produces the...
AI SafetyData & Datasets
Elo rating system (AI model ranking)
The Elo rating system, as applied to AI models, is a method for turning a pile of head-to-head preference votes into a single number per model, so that large...
AI BenchmarksMachine Learning
EnigmaEval
EnigmaEval is an AI benchmark of long, complex multimodal puzzles drawn from real-world puzzle hunts, designed to measure the unstructured, creative,...
AI Benchmarks
Epoch AI
Epoch AI is a nonprofit research organization, founded in 2022 and directed by Jaime Sevilla, that studies the trajectory of artificial intelligence through...
AI Companies
Expected calibration error
Expected calibration error (ECE) is a metric that measures how well a classifier's predicted confidence matches its observed accuracy. A model is well...
Machine LearningStatistics
F1 score
The F1 score (also written as F1-score, F-score, or F-measure) is the harmonic mean of precision and recall, calculated as , and it ranges from 0 (worst) to 1...
Machine LearningStatistics
FACTS Grounding
FACTS Grounding is a factuality benchmark from Google DeepMind and Google Research that measures whether a large language model answers a request using only...
AI BenchmarksLarge Language Models
FRAMES (benchmark)
FRAMES is an evaluation dataset for retrieval-augmented generation that tests factual accuracy, retrieval, and reasoning together rather than one at a time....
AI BenchmarksInformation Retrieval
Fairness Metric
A fairness metric is a quantitative, mathematical measure used to evaluate whether a machine learning model's predictions or decisions treat different...
AI EthicsMachine Learning
False Negative Rate
The false negative rate (FNR), also known as the miss rate, is the proportion of actual positive instances that a model or test incorrectly classifies as...
Machine LearningStatistics
False Positive Rate (FPR)
The false positive rate (FPR) is the proportion of actual negative cases that a test, model, or decision process incorrectly classifies as positive, defined as...
Machine LearningStatistics
False negative
A false negative (FN), also called a Type II error or a miss, is an instance whose true label is positive but that a classification model or test predicts as...
Machine LearningStatistics
False positive
A false positive (FP), also called a Type I error or a false alarm, is an instance whose true label is negative but whose predicted label is positive: the...
Machine LearningStatistics
Feature Importances
Feature importances are numeric scores that quantify how much each input feature contributes to the predictions of a machine learning model. The three dominant...
InterpretabilityMachine Learning
FormulaOne
FormulaOne is an AI benchmark for evaluating whether a model can design and implement dynamic programming algorithms for graph problems. Gal Beniamini and 12...
AI Benchmarks
Future of Life Institute AI Safety Index
The Future of Life Institute AI Safety Index (often shortened to the AI Safety Index or FLI AI Safety Index) is a periodic "report card" published by the...
AI Companies
Generalization
See also: Machine learning terms, Bias-variance tradeoff Generalization in machine learning is the ability of a trained model to perform accurately on new,...
Deep LearningMachine Learning
Generalization Curve
A generalization curve (also called a learning curve) is a plot that visualizes how a machine learning model's performance on training data and unseen data...
Machine Learning
Global-MMLU
Global-MMLU is a multilingual evaluation benchmark that extends the MMLU question-answering dataset across 42 languages, with designated subsets labeled...
AI BenchmarksNatural Language Processing
HELM (Holistic Evaluation of Language Models)
HELM (Holistic Evaluation of Language Models) is an open-source benchmark framework created by the Center for Research on Foundation Models (CRFM) at Stanford...
AI Benchmarks
HELMET
HELMET (How to Evaluate Long-context Models Effectively and Thoroughly) is a benchmark for evaluating long-context language models introduced by researchers at...
AI Benchmarks
HalluLens
HalluLens is a large language model hallucination benchmark introduced by researchers at Meta AI's Fundamental AI Research (FAIR) lab, together with...
AI BenchmarksMeta AI
Harness (AI)
This article is about software that wraps and evaluates AI models. For the 2015 paper "Explaining and Harnessing Adversarial Examples" and other uses of the...
AI AgentsAI Benchmarks
Helicone
Helicone is an open-source LLM observability platform and AI gateway founded in 2023 by Justin Torre, Cole Gottdank, Barak Oshri, and Scott...
AI CompaniesDeveloper Tools
Inter-rater agreement
See also: Machine learning terms Inter-rater agreement is the degree of consensus among two or more independent raters when they label or score the same set of...
Data & DatasetsStatistics
Interpretability
Interpretability in artificial intelligence concerns what people can learn about a system's behavior, predictions, or internal computations, and whether that...
AI EthicsMachine Learning
IoU
See also: Machine learning terms Intersection over Union (IoU), also known as the Jaccard index or Jaccard similarity coefficient, is the standard overlap...
Computer Vision
KernelBench
KernelBench is an AI benchmark and open-source evaluation environment that measures how well large language models can write fast and correct GPU kernels. The...
AI Benchmarks
LAB-Bench
LAB-Bench (the Language Agent Biology Benchmark) is an AI benchmark of more than 2,400 multiple-choice questions built to measure how well language models and...
AI Benchmarks
LLM API Pricing Comparison
Every figure in this article is a US dollar list rate per 1,000,000 tokens, taken from the provider's own pricing page and checked on August 1, 2026. That date...
AI Tools & ProductsLarge Language Models
LLM Benchmark Comparison (Leaderboard Overview)
As of July 2026, no single model wins every LLM benchmark, but Anthropic's Claude Fable 5 tops the most: it currently leads MMLU-Pro (91.5%), SWE-bench...
AI BenchmarksLarge Language Models