Unrecorded-weight games models
14
Models
10 organisations
—
Open weights
0 open, 0 closed
4
Frontier
By Epoch's flag
836,096
Largest traceable
DQN
1959–2017
Span
1 with a traceable size
Organisation
Records
14| Model | Organisation | Released | Parameters | Weights |
|---|---|---|---|---|
| OpenAI TI7 DOTA 1v1 | OpenAI | 2017-08 | — | Not recorded |
| HRA | Maluuba | 2017-06 | — | Not recorded |
| DeepStack | University of Alberta | 2017-01 | 3M * | Not recorded |
| A3C FF hs | 2016-02 | — | Not recorded | |
| Advantage Learning | Google DeepMind | 2015-12 | — | Not recorded |
| DQN-2015 | 2015-02 | 2M * | Not recorded | |
| SmooCT | University College London (UCL) | 2014-07 | — | Not recorded |
| HyperNEAT | University of Texas at Austin | 2014-03 | 239,712 * | Not recorded |
| DQN | DeepMind | 2013-12 | 836,096 | Not recorded |
| NeuroChess | 1994-12 | 72,251 * | Not recorded | |
| TD-Gammon | IBM | 1992-05 | 25,000 * | Not recorded |
| Boxes (pole) | University of Edinburgh | 1968-07 | — | Not recorded |
| GLEE | University of Edinburgh | 1968-07 | — | Not recorded |
| Samuel Neural Checkers | IBM | 1959-07 | 16 * | 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.