The AI Museum
AI Analytics1,072 recordsRecounted 23 September 2026

Unrecorded-weight models from Canada

26

Models

6 organisations

Open weights

0 open, 0 closed

5

Frontier

By Epoch's flag

140M

Largest traceable

Deep Autoencoders

1988–2017

Span

8 with a traceable size

Records

26
Unrecorded-weight models from Canada, newest first. Each row links to the source Epoch AI records for it.
ModelOrganisationReleasedParametersWeights
HRAMaluuba2017-06Not recorded
Prototypical networksUniversity of Toronto2017-03Not recorded
DeepStackUniversity of Alberta2017-013M *Not recorded
SC-NLMUniversity of Toronto2014-11Not recorded
GANsUniversity of Montreal / Université de Montréal2014-06Not recorded
GRUsUniversity of Montreal / Université de Montréal2014-06Not recorded
PreTrans-3L-250HUniversity of Toronto2013-0343M *Not recorded
Bayesian automated hyperparameter tuningUniversity of Toronto2012-12Not recorded
AlexNetUniversity of Toronto2012-0960MNot recorded
Deep AutoencodersUniversity of Toronto2011-04140MNot recorded
Deep rectifier networksUniversity of Montreal / Université de Montréal2011-04Not recorded
ReLU (LFW)University of Toronto2010-06Not recorded
ReLU (NORB)University of Toronto2010-0616M *Not recorded
Feedforward NNUniversity of Montreal / Université de Montréal2010-057MNot recorded
Stacked Denoising AutoencodersUniversity of Montreal / Université de Montréal2010-01Not recorded
Pragmatic Theory solution (Netflix 2009)Pragmatic Theory Inc.2009-08Not recorded
RBM Image ClassifierUniversity of Toronto2009-0480M *Not recorded
HLBLUniversity of Toronto2008-122MNot recorded
Denoising AutoencodersUniversity of Montreal / Université de Montréal2008-07Not recorded
Greedy layer-wise DNN trainingUniversity of Montreal / Université de Montréal2006-12Not recorded
Deep Belief NetsUniversity of Toronto2006-072M *Not recorded
Dimensionality ReductionUniversity of Toronto2006-074M *Not recorded
NPLM (AP News)University of Montreal / Université de Montréal2003-0312MNot recorded
NPLM (Brown)University of Montreal / Université de Montréal2003-034MNot recorded
Neural LMUniversity of Montreal / Université de Montréal2000-117MNot recorded
MLN-ASRMcGill University1988-0810,000Not 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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