Organization
Massachusetts Institute of Technology (MIT)
Tracked models
88
Frontier models
1
Largest training run
1.1 x 10^23 FLOP
88 tracked AI models list Massachusetts Institute of Technology (MIT) as a developer. 1 of them is frontier models — among the largest training runs of their moment. The largest is OpenVLA, at 1.1 x 10^23 FLOP (June 2024). The most recent tracked release is from November 2025.
It operates 1 tracked GPU cluster.
Models (80+)
OpenVLA1.1 x 10^23 FLOPStarCoder8.5 x 10^22 FLOPESM2-15B7.4 x 10^22 FLOPESM2-3B3 x 10^22 FLOPOmegaPLM10^22 FLOPESM2-650M7.6 x 10^21 FLOPHGRN2 1B6 x 10^21 FLOPGLM-10B4.9 x 10^21 FLOPRNA-FM2.6 x 10^21 FLOPVILA1.5-13B2.3 x 10^21 FLOPVILA-13B2.3 x 10^21 FLOPNVILA 8B2.3 x 10^21 FLOPSantaCoder2.1 x 10^21 FLOPHGRN2 3B1.7 x 10^21 FLOPAlphaflow1.6 x 10^21 FLOPESM2-150M1.1 x 10^21 FLOPGLA Transformer 1.3B7.8 x 10^20 FLOPESMFlow7.6 x 10^20 FLOPOnce for All6.2 x 10^20 FLOPTransformer-XL Large + Phrase Induction3.8 x 10^20 FLOPESM2-35M2.1 x 10^20 FLOPDiffDock7.2 x 10^19 FLOPESM2-8M4.8 x 10^19 FLOPGLA Transformer 340M3.1 x 10^19 FLOPHGRN 1B (WT 103)2 x 10^19 FLOPResNet-152 + ObjectNet1.9 x 10^19 FLOPImproved motif-scaffolding with SE(3) flow matching1.6 x 10^19 FLOPSSA1.3 x 10^19 FLOPEquiDock1.1 x 10^19 FLOPProxylessNAS3.7 x 10^18 FLOPCross-lingual alignment2.6 x 10^18 FLOPFlowER5.9 x 10^16 FLOPDiffDock-PP3.5 x 10^16 FLOPVine copula (breast cancer)8.5 x 10^15 FLOPVine copula (wine quality)8.5 x 10^15 FLOPVine copula (crime)8.5 x 10^15 FLOPiCCCP1.1 x 10^15 FLOPPandemonium (morse)6 x 10^8 FLOPOlmo 3 7B ThinkNovember 2025Olmo 3 32B InstructNovember 2025Olmo 3.1 32B ThinkNovember 2025MultiverSegAugust 2025Boltz-2June 2025SANA 1.5 4.8BMay 2025LinOSSMay 2025NVILA 15BDecember 2024Boltz-1November 2024SANA 1.6BOctober 2024BindCraftOctober 2024MdgenSeptember 2024CodonMPNNSeptember 2024CHIEFSeptember 2024LongVILA-7BAugust 2024ScribblePrompt-SAMJuly 2024MPNNsolJune 2024VILA1.5-40BMay 2024VILA-7BMay 2024AutoDiffApril 2024AyaFebruary 2024NAEProOctober 2023RFdiffusionJuly 2023OpenCLIP ViT-H-14-378-quickgeluApril 2023EigenFoldApril 2023UniPiJanuary 2023DiplodocusOctober 2022W2v-BERTAugust 2021DeepFRIMay 2021GLM-2BMarch 2021GLM-10B-unidirectionalMarch 2021GLM-10B-bidirectionalMarch 2021CryoDRGNFebruary 2021MicroNet (Adaptive, Cache)January 2020RNN BaselineJuly 2019AWD-LSTM + Phrase Induction + finetuning (PTB)June 2019Neuro-Symbolic Concept LearnerApril 2019BPLDecember 2015Skip-ThoughtsJune 2015RL mapping instructions (troubleshooting)August 2009RL mapping instructions (games)August 2009SACHSApril 2005
GPU clusters (1)
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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