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Models Released in 2019
Browse every generative AI model released in 2019 — large language models, image generators, code models and more — ordered by release date. Compare their specs and rankings on our benchmarks page, or put any two side by side with compare. See also models from 2018 and models from 2020.
FAIRSEQ Adaptive Inputs
🇺🇸 Facebook AI Research
SciBERT
🇺🇸 Allen Institute for AI
UniRep
🇺🇸 Harvard University
DOC + Finetune∗ + Partial Shuffle (PTB)
🇺🇸 University of Washington
NMT Transformer 437M
KataGo
🇺🇸 Jane Street
ProxylessNAS
🇺🇸 Massachusetts Institute of Technology (MIT)
SSA
🇺🇸 Massachusetts Institute of Technology (MIT)
code2seq
🇺🇸 Technion - Israel Institute of Technology
GPT-2 (1.5B)
🇺🇸 OpenAI
GPT-2 (124M)
🇺🇸 OpenAI
GPT-2 (355M)
🇺🇸 OpenAI
GPT-2 (774M)
🇺🇸 OpenAI
SDE
🇺🇸 Carnegie Mellon University (CMU)
Compress-LSTM (4.6M)
🇷🇺 Samsung R&D Institute Russia
Compress-LSTM (66M)
🇷🇺 Samsung R&D Institute Russia
Hanabi 4 player
🇬🇧 DeepMind
MT-DNN
🇺🇸 Microsoft
TSLM+MoS (PTB)
🇺🇸 Tianjin University
Mono3D++
🇺🇸 University of California Los Angeles (UCLA)
Transformer-XL (257M)
🇺🇸 Carnegie Mellon University (CMU)
Transformer-XL-ptb
🇺🇸 Carnegie Mellon University (CMU)
Decoupled weight decay regularization
🇩🇪 University of Freiburg
Transformer + Average Attention Network
🇺🇸 University of Electronic Science and Technology of China
Transformer ELMo
🇺🇸 Allen Institute for AI
2019 was another fast-moving year for generative AI. The models listed above span large language models (LLMs), image and video generators, code models and more, each with its own parameter count, context window, licensing and availability. To understand how the models of 2019 actually perform, compare their scores on our benchmarks page, and use compare to evaluate any two releases side by side.
Tracking AI by release year makes it easy to see how the frontier moves. Browse AI models from 2018 or AI models from 2020 to compare how capabilities, context windows and open-weights availability evolved year over year.