The AI Museum
AI Analytics1,072 recordsRecounted 23 September 2026

Unrecorded-weight frontier vision models

28

Models

18 organisations

Open weights

0 open, 0 closed

28

Frontier

By Epoch's flag

140M

Largest traceable

Deep Autoencoders

1960–2017

Span

17 with a traceable size

Records

28
Unrecorded-weight frontier vision models, newest first. Each row links to the source Epoch AI records for it.
ModelOrganisationReleasedParametersWeights
JFTGoogle Research2017-0745MNot recorded
NASv3 (CIFAR-10)Google Brain2016-1137M *Not recorded
XceptionGoogle2016-1023MNot recorded
Inception v3Google2015-1224M *Not recorded
MSRA (C, PReLU)Microsoft Research2015-0287MNot recorded
VGG16University of Oxford2014-09138MNot recorded
VGG19University of Oxford2014-09144M *Not recorded
SPPNetMicrosoft2014-06Not recorded
Visualizing CNNsNew York University (NYU)2013-11Not recorded
AlexNetUniversity of Toronto2012-0960MNot recorded
Unsupervised High-level Feature LearnerGoogle2012-071B *Not recorded
Deep AutoencodersUniversity of Toronto2011-04140MNot recorded
LCNP LabelMeUniversity of Bonn2009-1114MNot recorded
LCNP MNIST2009-1112MNot recorded
LMICA2004-124MNot recorded
Decision tree (classification)Mitsubishi Electric Research Labs2001-1212,000 *Not recorded
PoE MNISTUniversity College London (UCL)2000-114MNot recorded
LeNet-5AT&T1998-1160,000Not recorded
MUSIC perceptron1996-0613,607Not recorded
Siamese-TDNNBell Laboratories1993-08744 *Not recorded
SexNet compression1990-1072,940Not recorded
Zip CNNAT&T1989-129,760Not recorded
Handwritten digit recognition networkAT&T1989-112,578Not recorded
Invariant image recognitionComplutense University of Madrid1989-06Not recorded
NeocognitronNHK Broadcasting Science Research Laboratories1980-041MNot recorded
Print Recognition LogicIBM1963-01Not recorded
ADALINEStanford University1960-0617Not recorded
Perceptron (1960)Cornell Aeronautical Laboratory1960-031,000 *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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