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Models Released in 2021
Browse every generative AI model released in 2021 — 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 2020 and models from 2022.
Transformer local-attention (NesT-B)
🇺🇸 Google Cloud
ConSERT
🇨🇳 Meituan University
MedBERT
🇺🇸 Peng Cheng Laboratory
Multitask Unified Model (MUM)
Fairseq + UID: variance
🇺🇸 Google AI
ADM
🇺🇸 OpenAI
ProtBERT-BFD
🇺🇸 Technical University of Munich
ProtBERT-UniRef
🇺🇸 Technical University of Munich
ProtT5-XL-U50
🇺🇸 Technical University of Munich
ProtT5-XXL
🇺🇸 Technical University of Munich
ProtT5-XXL-BFD
🇺🇸 Technical University of Munich
Transformer-XL + SIS
🇺🇸 INRIA
GPT-J-6B
🇺🇸 EleutherAI
ViT + DINO
🇺🇸 INRIA
SPALM + kNN
🇬🇧 DeepMind
PanGu-α
🇨🇳 Huawei Noah's Ark Lab
DiffQ Transformer (16L)
🇺🇸 Meta AI
PLUG
🇨🇳 Alibaba
DLRM-12T
🇺🇸 Meta AI
Megatron-LM (1T)
🇺🇸 Microsoft Research
Transformer-C
🇺🇸 University of Massachusetts Amherst
GraphMS
🇨🇳 Dalian University of Technology
TransfoRNN(d=1024)(2-layer) (PTB)
🇨🇳 Lenovo Research
T2R + Pretrain
🇺🇸 University of Washington
T2R + Random Init
🇺🇸 University of Washington
T2R 75% + Pretrain (WT-103)
🇺🇸 University of Washington
Unicorn
🇺🇸 Allen Institute for AI
GPT-Neo-1.3B
🇺🇸 EleutherAI
GPT-Neo-1.3B (finetuned)
🇺🇸 EleutherAI
GPT-Neo-125M
🇺🇸 EleutherAI
GPT-Neo-125M (finetuned)
🇺🇸 EleutherAI
GPT-Neo-2.7B
🇺🇸 EleutherAI
GPT-Neo-2.7B (finetuned on PTB)
🇺🇸 EleutherAI
GPT-Neo-2.7B (finetuned)
🇺🇸 EleutherAI
U-Net GAN (FFHQ)
🇩🇪 Bosch Center for Artificial Intelligence
GLM-10B
🇨🇳 Tsinghua University
GLM-10B-bidirectional
🇨🇳 Tsinghua University
GLM-10B-unidirectional
🇨🇳 Tsinghua University
GLM-2B
🇨🇳 Tsinghua University
Very Deep VAEs (ImageNet-64)
🇺🇸 OpenAI
ResNet-RS
🇺🇸 Google Brain
AraELECTRA
🇱🇧 American University of Beirut
DCTransformer (ImageNet)
🇬🇧 DeepMind
Generative BST
🇺🇸 Facebook AI Research
M6-T
🇨🇳 Alibaba
ProteinGAN
🇱🇹 Vilnius University
RFA-GATE-Gaussian-Stateful Big
🇺🇸 University of Washington
Meta Pseudo Labels
🇺🇸 Google Brain
Wu Dao - Wen Hui
🇨🇳 Beijing Academy of Artificial Intelligence / BAAI
Wu Dao - Wen Lan
🇨🇳 Beijing Academy of Artificial Intelligence / BAAI
Wu Dao - Wen Su
🇨🇳 Beijing Academy of Artificial Intelligence / BAAI
SRU++ Base
🇺🇸 ASAPP
SRU++ Large
🇺🇸 ASAPP
SRU++ Large only 2 attention layers (k=5) (WT103)
🇺🇸 ASAPP
Linear Transformer (large)
🇨🇭 IDSIA
Linear Transformer (small)
🇨🇭 IDSIA
MSA Transformer
🇺🇸 Facebook AI Research
DLWP
🇺🇸 University of Washington
top-down frozen classifier
🇺🇸 University of Edinburgh
CryoDRGN
🇺🇸 Massachusetts Institute of Technology (MIT)
2021 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 2021 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 2020 or AI models from 2022 to compare how capabilities, context windows and open-weights availability evolved year over year.