The AI resource library

AI statistics, benchmarks & research.

Find the numbers behind the headlines, compare model performance, and understand how AI works. A curated collection of websites worth exploring.

50 information websites7 resource typesSources checked

50 of 50 websites

  • Benchmarks & leaderboards

    Artificial Analysis

    Compare AI models and hosting providers by benchmark results, speed, latency and price.

    Useful for Shortlisting models before testing your own workload.

    Reading note

    Read the methodology and configuration behind each comparison.

    artificialanalysis.aiVisit site
  • Benchmarks & leaderboards

    Arena

    Explore model leaderboards based on human preferences across supported text and media tasks.

    Useful for Seeing how users rate competing model outputs.

    Reading note

    Preference rankings depend on the voter pool, task mix and uncertainty.

    arena.aiVisit site
  • Statistics & trends

    Epoch AI

    Explore research and datasets on AI capability, compute, training and broader industry trends.

    Useful for Understanding the evidence behind AI progress claims.

    Reading note

    Check the date, definitions and uncertainty of each dataset.

    epoch.aiVisit site
  • Statistics & trends

    Stanford AI Index

    Read annual reports and supporting data about AI research, investment, adoption and social impact.

    Useful for Finding statistics for business plans and presentations.

    Reading note

    Annual reports describe a dated snapshot, not live market totals.

    hai.stanford.eduVisit site
  • Statistics & trends

    Our World in Data AI

    Browse charts, data and explanations about the development and impact of artificial intelligence.

    Useful for Finding understandable, source-linked AI statistics.

    Reading note

    Read each chart's underlying source and measurement notes.

    ourworldindata.orgVisit site
  • Policy & responsible AI

    OECD AI Policy Observatory

    Explore AI policy information, country activity and data from the OECD's AI observatory.

    Useful for Comparing AI policy developments across countries.

    Reading note

    Policy trackers are reference material; confirm current rules with the relevant authority.

  • Benchmarks & leaderboards

    HELM

    Explore Stanford's framework and results for evaluating language models across several dimensions.

    Useful for Looking beyond a single overall model score.

    Reading note

    Compare models within the same evaluation setting and version.

    crfm.stanford.eduVisit site
  • Benchmarks & leaderboards

    MLCommons

    Find standardised machine-learning benchmarks and published results for systems and workloads.

    Useful for Comparing AI hardware and system performance.

    Reading note

    Hardware, software and benchmark division affect comparability.

    mlcommons.orgVisit site
  • Benchmarks & leaderboards

    SWE-bench

    View software-engineering benchmark results based on resolving issues in real code repositories.

    Useful for Assessing coding agents on repository-level tasks.

    Reading note

    Check the benchmark variant, agent setup and evaluation rules.

    swebench.comVisit site
  • Benchmarks & leaderboards

    Terminal-Bench

    Explore evaluations of agents completing tasks in a terminal environment.

    Useful for Understanding command-line and agent-workflow capabilities.

    Reading note

    Results depend on the agent, model, tools and benchmark release.

    tbench.aiVisit site
  • Benchmarks & leaderboards

    LiveBench

    Compare language-model results across periodically refreshed evaluation tasks and releases.

    Useful for Checking performance across several task categories.

    Reading note

    Use the same release when comparing scores.

    livebench.aiVisit site
  • Benchmarks & leaderboards

    LiveCodeBench

    Explore coding-model evaluations built from time-stamped programming problems.

    Useful for Comparing coding performance with attention to data contamination.

    Reading note

    Task dates and evaluation windows affect the reported result.

    livecodebench.github.ioVisit site
  • Benchmarks & leaderboards

    SWE-rebench

    Browse a continuously refreshed software-engineering benchmark and its model results.

    Useful for Following coding-agent progress on newer repository tasks.

    Reading note

    Check the task set, date and agent configuration before comparing runs.

    swe-rebench.comVisit site
  • Benchmarks & leaderboards

    ARC Prize

    Explore reasoning benchmarks, public results and research competitions associated with ARC.

    Useful for Understanding evaluation of unfamiliar reasoning tasks.

    Reading note

    ARC results measure a specific task family, not all forms of intelligence.

    arcprize.orgVisit site
  • Benchmarks & leaderboards

    METR

    Read evaluations and research about advanced AI capabilities, autonomous work and associated risks.

    Useful for Understanding how longer agent tasks are evaluated.

    Reading note

    Read the experimental assumptions and uncertainty alongside the headline results.

    metr.orgVisit site
  • Benchmarks & leaderboards

    Vals AI

    Browse model evaluations across specialist domains and practical workflows.

    Useful for Finding domain-specific evidence when choosing an AI model.

    Reading note

    Read each benchmark's task design and scoring method.

  • Benchmarks & leaderboards

    SimpleBench

    View a benchmark focused on difficult everyday reasoning questions for language models.

    Useful for Exploring reasoning weaknesses that broad scores can hide.

    Reading note

    A narrow benchmark cannot establish overall model quality.

    simple-bench.comVisit site
  • Model & price trackers

    LLM Stats

    Browse model specifications, benchmark comparisons and pricing-oriented reference tables.

    Useful for Comparing models and identifying candidates to investigate.

    Reading note

    Composite scores and listed prices should be checked against their sources.

    llm-stats.comVisit site
  • Model & price trackers

    LLM Price Check

    Compare published language-model API prices across supported providers.

    Useful for Estimating which model APIs may fit a budget.

    Reading note

    Confirm current provider rates, caching rules and billing units before purchasing.

    llmpricecheck.comVisit site
  • Statistics & trends

    State of AI Report

    Read an annual overview of AI research, industry, policy and safety developments.

    Useful for Getting a broad overview of the AI ecosystem.

    Reading note

    Use the edition date when citing figures or conclusions.

    stateof.aiVisit site
  • Research libraries

    AI2 Research

    Browse research and publications from the Allen Institute for AI.

    Useful for Following work from a research organisation building open AI systems.

    Reading note

    Institutional research describes the authors' own work and priorities.

    allenai.orgVisit site
  • Research libraries

    arXiv AI

    Browse recent artificial-intelligence preprints and links to full papers.

    Useful for Tracking new research before formal publication.

    Reading note

    Preprints may not have completed peer review.

    arxiv.orgVisit site
  • Research libraries

    OpenReview

    Read research submissions, reviews and discussion where participating venues make them public.

    Useful for Checking both a paper and the surrounding review context.

    Reading note

    Submission and review visibility varies by venue.

    openreview.netVisit site
  • Research libraries

    Journal of Machine Learning Research

    Read openly accessible machine-learning research papers from JMLR.

    Useful for Finding detailed research with journal publication context.

    Reading note

    Technical papers may require statistical or machine-learning background.

    jmlr.orgVisit site
  • Research libraries

    Distill

    Explore visual and interactive explanations of machine-learning research.

    Useful for Developing intuition for technical concepts.

    Reading note

    This is an archive; check individual article dates.

    distill.pubVisit site
  • News & analysis

    The Gradient

    Read essays, interviews and analysis about AI research and its implications.

    Useful for Finding accessible perspectives on technical and social AI topics.

    Reading note

    Distinguish author commentary from primary research evidence.

    thegradient.pubVisit site
  • Research libraries

    Proceedings of Machine Learning Research

    Browse open proceedings from machine-learning conferences and workshops.

    Useful for Finding published papers by venue or volume.

    Reading note

    Review practices and scope vary between conferences and workshops.

    proceedings.mlr.pressVisit site
  • Research libraries

    NeurIPS Proceedings

    Search and read papers from NeurIPS proceedings and benchmark tracks.

    Useful for Exploring published work from a major machine-learning conference.

    Reading note

    Check the publication year and paper-specific evidence.

    proceedings.neurips.ccVisit site
  • Research libraries

    ICLR

    Find conference programmes, accepted research and links to ICLR proceedings.

    Useful for Following research on representation learning and related AI methods.

    Reading note

    Conference pages can point to different years; check the selected edition.

  • Research libraries

    ICML

    Find conference information, accepted papers and programme resources from ICML.

    Useful for Tracking machine-learning research and conference activity.

    Reading note

    Use the relevant conference year when citing work.

  • Research libraries

    ACL Anthology

    Search a large collection of computational-linguistics and natural-language-processing publications.

    Useful for Researching language technology and NLP methods.

    Reading note

    Read the original paper and venue details before relying on an abstract.

    aclanthology.orgVisit site
  • Research libraries

    OpenML

    Explore shared datasets, machine-learning tasks and experiment results.

    Useful for Finding datasets and reproducible evaluation material.

    Reading note

    Dataset licences, provenance and task definitions vary.

    openml.orgVisit site
  • Policy & responsible AI

    Center for Security and Emerging Technology

    Read data-led research on AI, emerging technology and public policy.

    Useful for Understanding AI investment, talent and strategic policy questions.

    Reading note

    Reports reflect their scope and publication date.

    cset.georgetown.eduVisit site
  • Policy & responsible AI

    AI Incident Database

    Explore documented reports of incidents involving AI systems and their impacts.

    Useful for Learning from reported failures and operational risks.

    Reading note

    Reports and classifications are not a complete or uniformly verified census.

    incidentdatabase.aiVisit site
  • Policy & responsible AI

    AIAAIC Repository

    Browse a repository of AI, algorithmic and automation incidents and controversies.

    Useful for Researching the social effects and reported harms of automated systems.

    Reading note

    Check the linked reporting and distinguish allegations from established facts.

    aiaaic.orgVisit site
  • Policy & responsible AI

    NIST AI Resource Center

    Find resources for AI risk management, evaluation and trustworthy deployment.

    Useful for Planning an organisation's approach to AI risk.

    Reading note

    Guidance is a framework for applying judgement, not an automatic compliance certificate.

    airc.nist.govVisit site
  • Policy & responsible AI

    Partnership on AI

    Read research, practice guidance and resources on responsible AI.

    Useful for Finding practical discussions of AI governance and impacts.

    Reading note

    Check the contributors, intended audience and scope of each resource.

    partnershiponai.orgVisit site
  • Policy & responsible AI

    GovAI

    Read research about governing increasingly capable AI systems.

    Useful for Understanding policy options and institutional challenges.

    Reading note

    Research recommendations are analysis, not enacted law.

    governance.aiVisit site
  • Policy & responsible AI

    AI Standards Hub

    Explore AI standards information, learning resources and community activity.

    Useful for Understanding standards relevant to AI development and governance.

    Reading note

    Confirm the version and applicability of any standard with its publisher.

    aistandardshub.orgVisit site
  • News & analysis

    Import AI

    Read a research-focused AI newsletter with commentary on technical and policy developments.

    Useful for Keeping up with research in an editorial digest.

    Reading note

    Follow links to original research; access conditions can vary by post.

    importai.substack.comVisit site
  • News & analysis

    AI as Normal Technology

    Read analysis of AI capabilities, limitations and societal effects from AI as Normal Technology.

    Useful for Examining claims about what AI can and cannot do.

    Reading note

    Commentary expresses the authors' analysis; consult the evidence they cite.

    normaltech.aiVisit site
  • News & analysis

    Interconnects

    Read technical commentary on language models, post-training and the AI research ecosystem.

    Useful for Following model-development ideas and research debates.

    Reading note

    Some posts may have subscriber access requirements.

    interconnects.aiVisit site
  • News & analysis

    The Batch

    Read a digest of AI news, research and industry developments from DeepLearning.AI.

    Useful for Getting a concise overview of recent AI developments.

    Reading note

    Check linked primary sources for the complete context.

    deeplearning.aiVisit site
  • Policy & responsible AI

    AI Now Institute

    Read research and policy analysis on the power, incentives and social effects of AI.

    Useful for Understanding institutional and societal questions around AI deployment.

    Reading note

    Policy analysis reflects a particular research perspective and publication date.

    ainowinstitute.orgVisit site
  • Visual explainers & learning

    Dive into Deep Learning

    Read an interactive deep-learning textbook with mathematical explanations and runnable examples.

    Useful for Studying how machine-learning models are built.

    Reading note

    Programming and mathematics background help; environment setup may be required.

  • Visual explainers & learning

    Full Stack Deep Learning

    Explore material about building and operating AI-powered products.

    Useful for Learning how model work connects to deployed applications.

    Reading note

    Check course and session dates because development practices change.

    fullstackdeeplearning.comVisit site
  • Visual explainers & learning

    LLM Visualization

    Explore a three-dimensional walkthrough of a language model's computation.

    Useful for Building a visual understanding of how a transformer processes text.

    Reading note

    The visualisation illustrates a particular model and simplifies the wider landscape.

    bbycroft.netVisit site
  • Visual explainers & learning

    Transformer Explainer

    Interact with a visual explanation of transformer components and text generation.

    Useful for Learning how attention and generation fit together.

    Reading note

    It is an educational demonstration, not a model-quality benchmark.

    poloclub.github.ioVisit site
  • Visual explainers & learning

    3Blue1Brown Neural Networks

    Watch visual mathematical explanations of neural networks and related ideas.

    Useful for Developing intuition before diving into implementation.

    Reading note

    Conceptual lessons do not replace hands-on training or current implementation guidance.

    3blue1brown.comVisit site
  • Visual explainers & learning

    The Illustrated Transformer

    Read a visual walkthrough of the original transformer architecture.

    Useful for Understanding attention and the foundations of language-model architecture.

    Reading note

    This is a foundational explanation; newer model designs differ.

    jalammar.github.ioVisit site