The AI Museum
AI Analytics1,072 recordsRecounted 23 September 2026

Models in 2016

Weightsopenclosedunknownfrontier only
Year20262025202420232022202120202019201820172016
1 filter active, showing 49 of 1,072 recordsClear all

49

Models

32 organisations

37%

Open weights

11 open, 19 closed

4

Frontier

By Epoch's flag

83M

Largest traceable

ResNeXt-101 (64×4d)

2016

Span

14 with a traceable size

Releases

by month
Jan
Feb
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Jun
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Organisation

Country

Domain

Records

49
Models in 2016, newest first. Each row links to the source Epoch AI records for it.
ModelOrganisationReleasedParametersWeights
3DMM-CNNUniversity of Southern California2016-1245MOpen
Elastic weight consolidationDeepMind2016-12—Not recorded
EnhanceNetMax Planck Institute for Intelligent Systems2016-12814,464Open
GAN-AdvancerOpenAI2016-12—Closed
HR-ResNet101Carnegie Mellon University (CMU)2016-1245MOpen
PointNetStanford University2016-12—Not recorded
YOLOv2University of Washington2016-1251M *Open
BIDAFUniversity of Washington2016-113MOpen
DAC-CSRJiangnan University2016-11—Closed
DLDL (PASCAL)University of Oxford2016-11564M *Open
DTN (Domain Transfer Network)Facebook AI Research2016-11—Closed
Image-to-image cGANUniversity of California (UC) Berkeley2016-11—Not recorded
NAS with base 8 and shared embeddingsGoogle Brain2016-1154MClosed
NASv3 (CIFAR-10)Google Brain2016-1137M *Not recorded
PolyNetChinese University of Hong Kong (CUHK)2016-1192M *Not recorded
ResNeXt-101 (64×4d)University of California San Diego2016-1183MOpen
ResNeXt-50University of California San Diego2016-1125M *Open
VD-LSTM+REAL LargeSalesforce Research2016-1151MClosed
GAWWNUniversity of Michigan2016-10—Closed
SPIDER2Griffith University2016-10409,536 *Open
XceptionGoogle2016-1023MNot recorded
GNMTGoogle2016-09278M *Closed
LF-MMIJohns Hopkins University2016-0917MClosed
MS-ensemble-speech-recognitionMicrosoft2016-093B *Closed
Pointer Sentinel-LSTM (medium)MetaMind Inc2016-0921MClosed
ResNet-1001Microsoft2016-0910M *Not recorded
ResNet-200Microsoft Research Asia2016-09—Closed
WaveNetGoogle DeepMind2016-09—Not recorded
Wide Residual NetworkUniversité Paris-Est2016-09—Not recorded
Youtube recommendation modelGoogle2016-09—Not recorded
DenseNet-264Tsinghua University2016-0834MOpen
SimpleNetSensifai2016-085MNot recorded
Character-enriched word2vecFacebook AI Research2016-07—Not recorded
CCLSenseTime2016-06—Closed
CMS-RCNNIEEE2016-06138M *Closed
PixelCNNGoogle DeepMind2016-06—Not recorded
R-FCNTsinghua University2016-06—Not recorded
Segmental RNNUniversity of Edinburgh2016-06—Closed
LRR-4XUC Irvine2016-05138M *Open
Dueling DQNGoogle DeepMind2016-042MClosed
Gated HORNN (3rd order)York University2016-049M *Closed
Double DQNGoogle DeepMind2016-032MClosed
Named Entity Recognition modelCarnegie Mellon University (CMU)2016-03—Not recorded
Template AdaptationUniversity of Oxford2016-03138M *Closed
A3C FF hsGoogle2016-02—Not recorded
Inception-ResNet-V2Google2016-0256M *Not recorded
Inceptionv4Google2016-0243M *Not recorded
SqueezeNetDeepScale2016-021M *Not recorded
AlphaGo LeeDeepMind2016-01—Closed

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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