The AI Museum
AI Analytics1,092 recordsRecounted 5 November 2026

Unrecorded-weight models in 2017

29

Models

25 organisations

—

Open weights

0 open, 0 closed

2

Frontier

By Epoch's flag

53M

Largest traceable

RetinaNet-R101

2017

Span

3 with a traceable size

Releases

by month
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec

Records

29
Unrecorded-weight models in 2017, newest first. Each row links to the source Epoch AI records for it.
ModelOrganisationReleasedParametersWeights
TriNetVisual Computing Institute2017-11—Not recorded
PhraseCondCarnegie Mellon University (CMU)2017-10—Not recorded
ProgressiveGANNvidia2017-10—Not recorded
S-NormUniversity of Washington2017-10—Not recorded
SENet (ImageNet)Chinese Academy of Sciences2017-0928M *Not recorded
NeuMF (Pinterest)Shandong University2017-08—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
GSMPeking University2017-07—Not recorded
JFTGoogle Research2017-0745MNot recorded
NASNet-AGoogle Brain2017-0789M *Not recorded
PSPNetChinese University of Hong Kong (CUHK)2017-07—Not recorded
ShuffleNet v1Megvii Inc2017-072M *Not recorded
DeepLabV3Google2017-06—Not recorded
EDSRSeoul National University2017-06—Not recorded
HRAMaluuba2017-06—Not recorded
Inflated 3D ConvNetDeepMind2017-06—Not recorded
PointNet++Stanford University2017-06—Not recorded
Reading Twice for NLUDeepMind2017-06—Not recorded
Mnemonic ReaderFudan University2017-05—Not recorded
DeepLab (2017)Johns Hopkins University2017-04—Not recorded
MobileNetGoogle2017-044M *Not recorded
Mask R-CNNFacebook AI Research2017-03—Not recorded
Prototypical networksUniversity of Toronto2017-03—Not recorded
DnCNNHarbin Institute of Technology2017-02—Not recorded
DeepStackUniversity of Alberta2017-013M *Not recorded
OR-WideResNetDuke University2017-0118MNot 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.

How this museum is made