{
  "generatedAt": "2026-07-18T00:55:13.689Z",
  "source": {
    "name": "Epoch AI — Notable AI Models",
    "publisher": "Epoch AI",
    "url": "https://epoch.ai/data/ai-models",
    "downloadUrl": "https://epoch.ai/data/notable_ai_models.csv",
    "docsUrl": "https://epoch.ai/data/ai-models-documentation",
    "license": "CC BY 4.0",
    "accessed": "2026-07-18",
    "caveat": "Training-compute figures are Epoch AI estimates with varying confidence; not all models report compute/cost/power."
  },
  "methodology": {
    "computeField": "Training compute (FLOP)",
    "doublingTimeMethod": "OLS regression of log10(training compute) on decimal year",
    "modernEraStart": 2010,
    "costUnit": "2023 USD",
    "notes": "Descriptive historical trends only — not a forecast.",
    "recentWindow": {
      "years": 3,
      "start": "2023-06-09",
      "end": "2026-06-09"
    }
  },
  "definitions": {
    "frontierDefinition": "Epoch AI's 'Frontier model' flag marks models in the top 10 by estimated training compute at the time of release. It reflects compute-disclosure availability and historical compute scale — not capability, quality, or societal impact. frontierCount is derived from compute-known rows only; models without compute estimates (including many recent and open-source releases) cannot carry this flag.",
    "orgLeaderboardMetric": "modelCount = all tracked Epoch AI rows with a valid publication date, regardless of compute disclosure. computeKnownCount = rows with training compute estimates. frontierCount = compute-known rows flagged as top-10 compute at release. recentCount = full-catalog models published within the 3-year recent window.",
    "countryLeaderboardDefaultSort": "Default sort: recentCount (full-catalog models in the recent window) descending. This reflects current tracked-output activity. frontierCount is provided for historical context but must not be used as a general country ranking.",
    "openWeightsMetric": "openWeightsCount derives from Epoch AI's 'Open model weights?' column ('Yes' = confirmed open weights). A proxy for tracked open-release activity only — not downloads, adoption, quality, or societal impact.",
    "multiCountryAttribution": "Models attributed to multiple countries are counted once per participating country (co-attribution). A single US–UK collaboration increments both country totals.",
    "googleEntitiesNote": "Google, DeepMind, Google Brain, Google Research, and Google DeepMind are preserved as distinct Epoch AI source entities. No editorial merger is applied.",
    "coverageNote": "Coverage is Epoch AI's 'Notable AI Models' curation — not an exhaustive registry. Labs without compute disclosure and newer open-source releases may be underrepresented in the compute-known subset."
  },
  "counts": {
    "totalRows": 1035,
    "withDate": 1030,
    "withCompute": 528,
    "withComputeAndDate": 528,
    "withPower": 215,
    "withCost": 179,
    "withOpenWeights": 318,
    "countries": 35,
    "recentWindowStart": "2023-06-09",
    "recentWindowEnd": "2026-06-09",
    "recentWindowCount": 317
  },
  "models": [
    {
      "name": "Theseus",
      "organization": "Bell Laboratories",
      "orgCategory": "Industry",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1950-07-02",
      "year": 1950,
      "decimalYear": 1950.49863,
      "domains": [
        "Robotics"
      ],
      "task": "Maze solving",
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      "computeFlop": 40,
      "log10Compute": 1.602,
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      "frontier": true,
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      "accessibility": null,
      "confidence": "Confident",
      "link": "https://www.technologyreview.com/2018/12/19/138508/mighty-mouse/"
    },
    {
      "name": "Perceptron Mark I",
      "organization": "Cornell Aeronautical Laboratory,Cornell University",
      "orgCategory": "Academia,Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1957-01-01",
      "year": 1957,
      "decimalYear": 1957,
      "domains": [
        "Other"
      ],
      "task": "Binary classification",
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      "confidence": "Likely",
      "link": "https://blogs.umass.edu/brain-wars/files/2016/03/rosenblatt-1957.pdf"
    },
    {
      "name": "Pandemonium (morse)",
      "organization": "Massachusetts Institute of Technology (MIT)",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1959-02-01",
      "year": 1959,
      "decimalYear": 1959.084932,
      "domains": [
        "Language"
      ],
      "task": "Morse translation",
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      "computeFlop": 600000000,
      "log10Compute": 8.778,
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      "frontier": true,
      "openWeights": null,
      "accessibility": null,
      "confidence": "Speculative",
      "link": "https://aitopics.org/doc/classics:504E1BAC/"
    },
    {
      "name": "Samuel Neural Checkers",
      "organization": "IBM",
      "orgCategory": "Industry",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1959-07-01",
      "year": 1959,
      "decimalYear": 1959.49589,
      "domains": [
        "Games"
      ],
      "task": "Checkers",
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      "accessibility": null,
      "confidence": "Likely",
      "link": "https://ieeexplore.ieee.org/abstract/document/5392560"
    },
    {
      "name": "Perceptron (1960)",
      "organization": "Cornell Aeronautical Laboratory",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1960-03-30",
      "year": 1960,
      "decimalYear": 1960.243169,
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        "Vision"
      ],
      "task": "Image classification",
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      "confidence": "Speculative",
      "link": "https://www.semanticscholar.org/paper/Perceptron-Simulation-Experiments-Rosenblatt/ae76ce1ba27ac29addce4aab93b927e9bc7f7c67"
    },
    {
      "name": "ADALINE",
      "organization": "Stanford University",
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      "countries": [
        "United States"
      ],
      "date": "1960-06-30",
      "year": 1960,
      "decimalYear": 1960.494536,
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        "Vision"
      ],
      "task": "Pattern recognition",
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      "confidence": "Confident",
      "link": "https://isl.stanford.edu/~widrow/papers/c1960adaptiveswitching.pdf"
    },
    {
      "name": "Linear Decision Functions",
      "organization": "Bell Laboratories",
      "orgCategory": "Industry",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1962-06-01",
      "year": 1962,
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        "Mathematics"
      ],
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      "confidence": "Speculative",
      "link": "https://ieeexplore.ieee.org/document/4066882?denied="
    },
    {
      "name": "Print Recognition Logic",
      "organization": "IBM",
      "orgCategory": "Industry",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1963-01-01",
      "year": 1963,
      "decimalYear": 1963,
      "domains": [
        "Vision"
      ],
      "task": "Character recognition (OCR)",
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      "confidence": "Speculative",
      "link": "https://ieeexplore.ieee.org/document/5392331"
    },
    {
      "name": "Heuristic Reinforcement Learning",
      "organization": "Purdue University",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1965-10-01",
      "year": 1965,
      "decimalYear": 1965.747945,
      "domains": [
        "Robotics"
      ],
      "task": "System control",
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      "computeFlop": 1080000,
      "log10Compute": 6.033,
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      "confidence": "Speculative",
      "link": "https://ieeexplore.ieee.org/document/1098193"
    },
    {
      "name": "LTE speaker verification system",
      "organization": "IBM",
      "orgCategory": "Industry",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1966-11-01",
      "year": 1966,
      "decimalYear": 1966.832877,
      "domains": [
        "Speech"
      ],
      "task": "Speech recognition (ASR)",
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      "confidence": "Likely",
      "link": "https://pubs.aip.org/asa/jasa/article-abstract/40/5/966/754180/Experimental-Studies-in-Speaker-Verification-Using?redirectedFrom=fulltext"
    },
    {
      "name": "Cognitron",
      "organization": "Biological Cybernetics",
      "orgCategory": "Industry",
      "country": "Japan",
      "countries": [
        "Japan"
      ],
      "date": "1975-09-01",
      "year": 1975,
      "decimalYear": 1975.665753,
      "domains": [
        "Other"
      ],
      "task": "Miscellaneous image analysis,Image classification",
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      "confidence": "Confident",
      "link": "https://link.springer.com/article/10.1007%2FBF00342633"
    },
    {
      "name": "Neocognitron",
      "organization": "NHK Broadcasting Science Research Laboratories",
      "orgCategory": "Industry",
      "country": "Japan",
      "countries": [
        "Japan"
      ],
      "date": "1980-04-01",
      "year": 1980,
      "decimalYear": 1980.248634,
      "domains": [
        "Vision"
      ],
      "task": "Character recognition (OCR)",
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      "confidence": "Confident",
      "link": "https://link.springer.com/article/10.1007/BF00344251"
    },
    {
      "name": "ASE+ACE",
      "organization": "University of Massachusetts Amherst",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1983-09-01",
      "year": 1983,
      "decimalYear": 1983.665753,
      "domains": [
        "Robotics"
      ],
      "task": "Pole balancing",
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      "computeFlop": 324000000,
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      "confidence": "Likely",
      "link": "https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6313077"
    },
    {
      "name": "Distributed representation NN",
      "organization": "Carnegie Mellon University (CMU)",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1986-08-15",
      "year": 1986,
      "decimalYear": 1986.619178,
      "domains": [
        "Other"
      ],
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      "confidence": "Confident",
      "link": "https://www.cs.toronto.edu/~hinton/absps/families.pdf"
    },
    {
      "name": "MLP with back-propagation",
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      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1986-10-01",
      "year": 1986,
      "decimalYear": 1986.747945,
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        "Mathematics"
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    },
    {
      "name": "NetTalk (transcription)",
      "organization": "Princeton University",
      "orgCategory": "Academia",
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      "countries": [
        "United States"
      ],
      "date": "1987-06-06",
      "year": 1987,
      "decimalYear": 1987.427397,
      "domains": [
        "Speech"
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      "task": "Speech synthesis",
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      "link": "http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=03A3D3EDF0BAF35405ABCF083411B55E?doi=10.1.1.154.7012&rep=rep1&type=pdf"
    },
    {
      "name": "NetTalk (dictionary)",
      "organization": "Princeton University",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1987-06-06",
      "year": 1987,
      "decimalYear": 1987.427397,
      "domains": [
        "Speech"
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      "task": "Speech synthesis",
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      "link": "http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=03A3D3EDF0BAF35405ABCF083411B55E?doi=10.1.1.154.7012&rep=rep1&type=pdf"
    },
    {
      "name": "Translation-invariant MLP",
      "organization": "Carnegie Mellon University (CMU)",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1987-06-15",
      "year": 1987,
      "decimalYear": 1987.452055,
      "domains": [],
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      "link": "https://www.cs.toronto.edu/~hinton/absps/parle.pdf"
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    {
      "name": "MLN-ASR",
      "organization": "McGill University",
      "orgCategory": "Academia",
      "country": "Canada",
      "countries": [
        "Canada"
      ],
      "date": "1988-08-01",
      "year": 1988,
      "decimalYear": 1988.581967,
      "domains": [
        "Speech"
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      "task": "Speech recognition (ASR)",
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      "accessibility": null,
      "confidence": "Confident",
      "link": "https://aaai.org/papers/00734-aaai88-130-data-driven-execution-of-multi-layered-networks-for-automatic-speech-recognition/"
    },
    {
      "name": "Invariant image recognition",
      "organization": "Complutense University of Madrid",
      "orgCategory": "Academia",
      "country": "Spain",
      "countries": [
        "Spain"
      ],
      "date": "1989-06-18",
      "year": 1989,
      "decimalYear": 1989.460274,
      "domains": [
        "Vision"
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      "link": "https://ieeexplore.ieee.org/document/118669"
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    {
      "name": "Speaker-independent vowel classification",
      "organization": "University of Washington",
      "orgCategory": "Academia",
      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1989-11-27",
      "year": 1989,
      "decimalYear": 1989.90411,
      "domains": [
        "Speech"
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      "link": "https://www.semanticscholar.org/paper/Performance-Comparisons-Between-Backpropagation-and-Atlas-Cole/e42d2b89fcb4a1a3dfa63408f424f76975ed1e1b"
    },
    {
      "name": "Handwritten digit recognition network",
      "organization": "AT&T",
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      "country": "United States",
      "countries": [
        "United States"
      ],
      "date": "1989-11-27",
      "year": 1989,
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    {
      "name": "Zip CNN",
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      ],
      "date": "1989-12-01",
      "year": 1989,
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      "link": "https://ieeexplore.ieee.org/document/6795724"
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    {
      "name": "NETtalk reimplementation",
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        "United States"
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      "confidence": "Confident",
      "link": "https://www.sciencedirect.com/science/article/abs/pii/B9781558601413500079"
    },
    {
      "name": "Bankruptcy-NN",
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      "countries": [],
      "date": "1990-06-17",
      "year": 1990,
      "decimalYear": 1990.457534,
      "domains": [
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      "confidence": "Confident",
      "link": "https://www.semanticscholar.org/paper/A-neural-network-model-for-bankruptcy-prediction-Odom-Sharda/ead9fa02902850a7418fb5ba720f3d9d8ab2f88b"
    },
    {
      "name": "SexNet compression",
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      "country": null,
      "countries": [],
      "date": "1990-10-01",
      "year": 1990,
      "decimalYear": 1990.747945,
      "domains": [
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      "confidence": "Confident",
      "link": "https://www.semanticscholar.org/paper/SEXNET%3A-A-Neural-Network-Identifies-Sex-From-Human-Golomb-Lawrence/cbf90aa78fea0c8a1028705d92bc4bc7808ddeeb"
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    {
      "name": "Weight Decay",
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      "date": "1991-12-02",
      "year": 1991,
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      "domains": [
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        "openWeightsCount": 0,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Austria",
        "countryShort": "Austria",
        "iso3": "AUT",
        "modelCount": 1,
        "computeKnownCount": 0,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 1,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Croatia",
        "countryShort": "Croatia",
        "iso3": "HRV",
        "modelCount": 1,
        "computeKnownCount": 0,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 0,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Iran",
        "countryShort": "Iran",
        "iso3": "IRN",
        "modelCount": 1,
        "computeKnownCount": 0,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 0,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Ireland",
        "countryShort": "Ireland",
        "iso3": "IRL",
        "modelCount": 1,
        "computeKnownCount": 1,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 0,
        "maxComputeFlop": 34153451000000000,
        "orgCount": 1
      },
      {
        "country": "Malaysia",
        "countryShort": "Malaysia",
        "iso3": "MYS",
        "modelCount": 1,
        "computeKnownCount": 0,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 0,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Norway",
        "countryShort": "Norway",
        "iso3": "NOR",
        "modelCount": 1,
        "computeKnownCount": 0,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 1,
        "maxComputeFlop": 0,
        "orgCount": 1
      },
      {
        "country": "Russia",
        "countryShort": "Russia",
        "iso3": "RUS",
        "modelCount": 1,
        "computeKnownCount": 1,
        "frontierCount": 0,
        "recentCount": 0,
        "openWeightsCount": 0,
        "maxComputeFlop": 51880000000000000,
        "orgCount": 1
      }
    ],
    "accessibilityMix": {
      "openWeights": 219,
      "closed": 211,
      "unknown": 98
    },
    "fullCatalogAccessibilityMix": {
      "openWeights": 318,
      "closed": 452,
      "unknown": 260
    },
    "domainMix": [
      {
        "domain": "Language",
        "count": 299
      },
      {
        "domain": "Vision",
        "count": 147
      },
      {
        "domain": "Multimodal",
        "count": 41
      },
      {
        "domain": "Biology",
        "count": 34
      },
      {
        "domain": "Games",
        "count": 27
      },
      {
        "domain": "Speech",
        "count": 22
      },
      {
        "domain": "Image generation",
        "count": 21
      },
      {
        "domain": "Video",
        "count": 13
      },
      {
        "domain": "Robotics",
        "count": 10
      },
      {
        "domain": "Earth science",
        "count": 7
      },
      {
        "domain": "Other",
        "count": 7
      },
      {
        "domain": "Audio",
        "count": 5
      },
      {
        "domain": "Mathematics",
        "count": 4
      },
      {
        "domain": "Medicine",
        "count": 2
      },
      {
        "domain": "Search",
        "count": 2
      },
      {
        "domain": "Materials science",
        "count": 1
      },
      {
        "domain": "Recommendation",
        "count": 1
      }
    ]
  },
  "caveats": [
    "Coverage is not exhaustive; Epoch curates 'notable' models.",
    "Compute estimates carry uncertainty (see Confidence field).",
    "Future-dated entries reflect the source snapshot and are shown as-is.",
    "Descriptive trends, not predictions.",
    "Multi-country collaboration models are co-attributed to each participating country in the country leaderboard.",
    "Epoch AI's 'Frontier model' flag reflects top-10 training compute at release time, not capability or impact.",
    "Org/country model counts use the full dated catalog. Compute-derived metrics (frontierCount, maxComputeFlop) use only the compute-known subset.",
    "openWeightsCount is a proxy for tracked open-release activity only."
  ],
  "meta": {
    "generatedAt": "2026-07-18T00:55:13.689Z",
    "asOf": "2026-07-18",
    "source": {
      "name": "Epoch AI — Notable AI Models",
      "publisher": "Epoch AI",
      "url": "https://epoch.ai/data/ai-models"
    },
    "version": "1.0.0"
  }
}
