The AI Museum
AI Analytics1,092 recordsRecounted 5 November 2026

Unrecorded-weight models from United States of America

Weightsopenclosedunknownfrontier only
Year20262025202420232022202120202019201820172016
2 filters active, showing 150 of 1,092 recordsClear all

150

Models

46 organisations

—

Open weights

0 open, 0 closed

37

Frontier

By Epoch's flag

2B

Largest traceable

Seq2Seq LSTM

1950–2026

Span

32 with a traceable size

Releases

by year, from 2011
2011201220132014201520162017201820192020202120222023202420252026

Organisation

Country

Domain

Records

newest 50 of 150
Unrecorded-weight models from United States of America, newest first. Each row links to the source Epoch AI records for it.
ModelOrganisationReleasedParametersWeights
Gemini 4 ArgonGoogle DeepMind2026-09—Not recorded
Claude Mythos PreviewAnthropic2026-04—Not recorded
GPT-5.4-CyberOpenAI2026-04—Not recorded
MaskGIT (ImageNet)Google Research2022-02227MNot recorded
GPipe (Transformer)Google2018-116B *Not recorded
MetaMimicGoogle2018-1022M *Not recorded
MobileNetV2Google2018-063M *Not recorded
Chinese - English translationMicrosoft2018-03—Not recorded
DeepLabV3+Google2018-02—Not recorded
ELMoUniversity of Washington2018-0294M *Not recorded
TCN (P-MNIST)Carnegie Mellon University (CMU)2018-0242,000Not recorded
PhraseCondCarnegie Mellon University (CMU)2017-10—Not recorded
ProgressiveGANNvidia2017-10—Not recorded
S-NormUniversity of Washington2017-10—Not recorded
OpenAI TI7 DOTA 1v1OpenAI2017-08—Not recorded
RetinaNet-R101Facebook AI Research2017-0853MNot recorded
RetinaNet-R50Facebook AI Research2017-0834M *Not recorded
ConvS2S (ensemble of 8 models)Meta AI2017-07—Not recorded
JFTGoogle Research2017-0745MNot recorded
NASNet-AGoogle Brain2017-0789M *Not recorded
DeepLabV3Google2017-06—Not recorded
PointNet++Stanford University2017-06—Not recorded
DeepLab (2017)Johns Hopkins University2017-04—Not recorded
MobileNetGoogle2017-044M *Not recorded
Mask R-CNNFacebook AI Research2017-03—Not recorded
OR-WideResNetDuke University2017-0118MNot recorded
PointNetStanford University2016-12—Not recorded
Image-to-image cGANUniversity of California (UC) Berkeley2016-11—Not recorded
NASv3 (CIFAR-10)Google Brain2016-1137M *Not recorded
XceptionGoogle2016-1023MNot recorded
ResNet-1001Microsoft2016-0910M *Not recorded
WaveNetGoogle DeepMind2016-09—Not recorded
Youtube recommendation modelGoogle2016-09—Not recorded
Character-enriched word2vecFacebook AI Research2016-07—Not recorded
PixelCNNGoogle DeepMind2016-06—Not recorded
Named Entity Recognition modelCarnegie Mellon University (CMU)2016-03—Not recorded
A3C FF hsGoogle2016-02—Not recorded
Inception-ResNet-V2Google2016-0256M *Not recorded
Inceptionv4Google2016-0243M *Not recorded
SqueezeNetDeepScale2016-021M *Not recorded
Advantage LearningGoogle DeepMind2015-12—Not recorded
Inception v3Google2015-1224M *Not recorded
Netflix Recommender SystemNetflix2015-12—Not recorded
ResNet-110 (CIFAR-10)Microsoft2015-122M *Not recorded
ResNet-152 (ImageNet)Microsoft2015-1260MNot recorded
Multi-scale Dilated CNNPrinceton University2015-11—Not recorded
Deep Deterministic Policy GradientsGoogle DeepMind2015-09—Not recorded
BatchNormGoogle2015-0614MNot recorded
YOLOUniversity of Washington2015-06272M *Not recorded
Fast R-CNNMicrosoft Research2015-04—Not recorded

An asterisk marks a parameter figure the source does not consider traceable to the people who built the model. That judgement is the source’s and it has false negatives: Kimi K3 is marked speculative at 2.8T while Moonshot’s own model card states the figure. Why that distinction carries the whole exhibit.

Counts are of models Epoch AI records as notable, not of every model released. The most recent month is always incomplete, because a model enters the dataset when it is reviewed rather than when it ships.

Epoch AI, 'Data on AI Models'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/data/ai-models-documentation' Used under CC BY 4.0.

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