Awesome AI Benchmarks & Evaluation

       

A curated list of evaluation tools, benchmark datasets, leaderboards, frameworks, and resources for assessing model performance across reasoning, safety, robustness, multimodality, RAG, LLMs, and traditional machine learning tasks.

Contents

• General LLM Benchmarks
• Reasoning & Math
• Multimodal Benchmarks
• RAG Benchmarks
• Safety & Robustness
• Evaluation Frameworks
• Datasets
• Learning Resources
• Related Awesome Lists

General LLM Benchmarks

• HELM – Holistic evaluation of LLMs across dozens of tasks and domains.
• LM Evaluation Harness – Standardized benchmarking suite for language models.
• OpenLLM Leaderboard (HuggingFace) – Public leaderboard for open-source LLM performance.
• BIG-Bench – Broad set of challenging tasks for evaluating model generalization.
• MT-Bench – Multi-turn chat interaction benchmark.
• AlpacaEval – Automatic evaluation of instruction-following models.

Reasoning & Math

• GSM8K – Benchmark for math reasoning at grade-school level.
• MATH – Extensive dataset of high school and competition math problems.
• AIME Bench – Benchmark based on American Invitational Mathematics Examination questions.
• ARC (Abstraction & Reasoning Corpus) – Tests generalization and abstraction capabilities.
• AGIEval – Benchmarks for human-style exams and reasoning.

Multimodal Benchmarks

• MMBench – Large benchmark for vision–language reasoning.
• COCO Captions & VQA – Standard dataset for VQA tasks.
• Flickr30k – Image–text benchmark for captioning and retrieval.
• ImageNet – Core image classification benchmark still used for comparison.
• LAION Benchmarks – Evaluation datasets for multimodal embeddings and retrieval.
• Video Question Answering Benchmarks – For video–text reasoning.

RAG Benchmarks

• RAGAS – Comprehensive metrics for evaluating retrieval-augmented generation.
• BEIR – Retrieval benchmark widely used to test search quality in RAG systems.
• FiQA / TREC Variants – Evaluation datasets for information retrieval tasks.
• Natural Questions (NQ) – Large dataset for retrieval + QA evaluation.
• HotpotQA – Multi-hop question answering benchmark.

Safety & Robustness

• HarmBench – Safety and harm classification benchmark.
• SafetyBench – Benchmark suite for safety testing.
• ToxiGen – Dataset for toxic or harmful content detection.
• Red Team Prompt Datasets – Collections of prompts to stress-test model alignment.
• RobustBench – Leaderboard of robust classification models.
• AdversarialNLI – Dataset for robustness in natural language inference.

Evaluation Frameworks

• OpenAI Evals – Evaluation framework for custom metrics and tasks.
• TruLens – Observability and feedback evaluation for LLM apps and RAG.
• Arize Phoenix – Open-source toolkit for LLM/RAG evals and trace analysis.
• LightEval – Fast LLM evaluation pipeline.
• Evalchemy – Lightweight framework for running LLM benchmarks.
• Weights & Biases Evaluation – Model comparison and metric visualization tools.

Datasets

• TruthfulQA – Benchmark for truthfulness in open-ended QA.
• SQuAD – Reading comprehension dataset.
• BoolQ – Yes/no question dataset.
• SuperGLUE – General NLU evaluation suite.
• MultiRC – Multi-sentence reasoning benchmark.
• WikiQA – QA benchmark used in retrieval + QA systems.
• CommonSenseQA – Commonsense reasoning dataset.

Learning Resources

• HELM Overview – Intro to full-spectrum model benchmarking.
• LLM Evaluation Guide (HuggingFace) – End-to-end guide for evaluating language models.
• Stanford CS25 Notes – Covers benchmarking and model evaluation basics.
• MLPerf – Industry-standard ML performance benchmarking guidelines.
• DeepMind Papers on Evaluation – Research on model testing and evaluation.

Related Awesome Lists

• Awesome AI
• Awesome AI Safety & Alignment
• Awesome AI Security
• Awesome AI Research Tools
• Awesome Machine Learning

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Contributions are welcome!

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