AI Safety Tracker

Training compute over time

Every notable model with a reported or estimated training-compute figure, on a logarithmic scale. Each step of the axis is ten times the one below it.

1e141e161e181e201e221e241e26201220142016201820202022202420261e25 FLOP, EU AI Act Article 51Dropout (MNIST) (University of Toronto, 2012-06-03): 6.0e15 FLOP, confidence ConfidentDropout (ImageNet) (University of Toronto, 2012-06-03): 2.7e17 FLOP, confidence ConfidentDropout (CIFAR) (University of Toronto, 2012-06-03): 4.3e15 FLOP, confidence ConfidentUnsupervised High-level Feature Learner (Google, 2012-07-12): 6.0e17 FLOP, confidence LikelyLSTM LM (RWTH Aachen University, 2012-09-09): 1.7e16 FLOP, confidence SpeculativeAlexNet (University of Toronto, 2012-09-30): 4.7e17 FLOP, confidence ConfidentDNN EM segmentation (IDSIA,SUPSI, 2012-12-03): 4.8e17 FLOP, confidence ConfidentDistBelief Speech (Google, 2012-12-03): 3.1e17 FLOP, confidence SpeculativeDistBelief NNLM (Google, 2013-01-16): 2.6e18 FLOP, confidence LikelyReLU-Speech (Google,University of Toronto,New York University (NYU), 2013-05-26): 1.3e17 FLOP, confidence LikelyHierarchical Scene Labeling (Stanford Background) (New York University (NYU), 2013-08-01): 2.4e17 FLOP, confidence ConfidentRNTN (Stanford University, 2013-10-01): 1.4e16 FLOP, confidence LikelyRCTM (University of Oxford, 2013-10-01): 9.3e15 FLOP, confidence LikelyWord2Vec (large) (Google, 2013-10-16): 3.9e16 FLOP, confidence LikelyVisualizing CNNs (New York University (NYU), 2013-11-12): 5.3e17 FLOP, confidence ConfidentTransE (Universite de Technologie de Compiègne - CNRS,Google, 2013-12-05): 1.3e18 FLOP, confidence SpeculativeDQN (DeepMind, 2013-12-19): 2.8e15 FLOP, confidence ConfidentImage generation (University of Amsterdam, 2013-12-20): 4.8e14 FLOP, confidence ConfidentGANs (University of Montreal / Université de Montréal, 2014-06-10): 5.2e17 FLOP, confidence SpeculativeSPPNet (Microsoft,Xi’an Jiaotong University,University of Science and Technology of China (USTC), 2014-06-18): 3.4e18 FLOP, confidence ConfidentSmooCT (University College London (UCL), 2014-07-01): 6.9e16 FLOP, confidence LikelyACF-WIDER (Chinese Academy of Sciences, 2014-07-15): 7.6e13 FLOP, confidence ConfidentRNNsearch-50* (Jacobs University Bremen,University of Montreal / Université de Montréal, 2014-09-01): 1.6e18 FLOP, confidence ConfidentVGG19 (University of Oxford, 2014-09-04): 1.1e19 FLOP, confidence LikelyVGG16 (University of Oxford, 2014-09-04): 1.2e19 FLOP, confidence ConfidentSeq2Seq LSTM (Google, 2014-09-10): 5.6e19 FLOP, confidence ConfidentSPN-4+KN5 (Singapore University of Technology & Design,DSO National Laboratories, 2014-09-14): 4.4e16 FLOP, confidence LikelyGoogLeNet / InceptionV1 (Google,University of Michigan,University of North Carolina, 2014-09-17): 1.5e18 FLOP, confidence ConfidentTA-CNN (Chinese University of Hong Kong (CUHK), 2014-11-29): 1.1e16 FLOP, confidence LikelySNM-skip (Google, 2014-12-03): 3.0e20 FLOP, confidence SpeculativeFractional Max-Pooling (University of Warwick, 2014-12-18): 1.0e17 FLOP, confidence LikelyADAM (CIFAR-10) (University of Amsterdam,OpenAI,University of Toronto, 2014-12-22): 6.2e14 FLOP, confidence ConfidentMSRA (C, PReLU) (Microsoft Research, 2015-02-06): 2.4e19 FLOP, confidence ConfidentgenCNN + dyn eval (Chinese Academy of Sciences,Huawei Noah's Ark Lab,Dublin City University, 2015-03-17): 3.4e16 FLOP, confidence SpeculativeTC-DNN-BLSTM-DNN (Carnegie Mellon University (CMU), 2015-04-06): 1.9e17 FLOP, confidence ConfidentU-Net (University of Freiburg, 2015-05-18): 5.1e16 FLOP, confidence ConfidentDCNN (University of Maryland,Rutgers University, 2015-08-07): 4.8e17 FLOP, confidence ConfidentAlphaGo Fan (DeepMind, 2015-10-01): 3.8e20 FLOP, confidence LikelySAF R-CNN (Beijing Institute of Technology,Sun Yat-sen University,Panasonic R&D,National University of Singapore, 2015-10-28): 1.2e19 FLOP, confidence LikelyInception v3 (Google,University College London (UCL), 2015-12-02): 1.0e20 FLOP, confidence LikelyResNet-152 (ImageNet) (Microsoft, 2015-12-10): 1.0e19 FLOP, confidence ConfidentResNet-101 (ImageNet) (Microsoft, 2015-12-10): 7.0e18 FLOP, confidence ConfidentVariational (untied weights, MC) LSTM (Large) (University of Cambridge, 2015-12-16): 5.9e15 FLOP, confidence ConfidentAlphaGo Lee (DeepMind, 2016-01-27): 1.9e21 FLOP, confidence SpeculativeNamed Entity Recognition model (Carnegie Mellon University (CMU), 2016-03-04): 9.7e16 FLOP, confidence ConfidentR-FCN (Tsinghua University,Microsoft Research, 2016-06-21): 7.2e17 FLOP, confidence ConfidentResNet-200 (Microsoft Research Asia, 2016-09-17): 3.0e19 FLOP, confidence SpeculativePointer Sentinel-LSTM (medium) (MetaMind Inc,Salesforce, 2016-09-26): 7.5e15 FLOP, confidence ConfidentGNMT (Google, 2016-09-26): 6.6e21 FLOP, confidence LikelyXception (Google, 2016-10-07): 4.4e20 FLOP, confidence ConfidentSPIDER2 (Griffith University,University of Iowa,Dezhou University, 2016-10-28): 1.8e16 FLOP, confidence LikelyVD-LSTM+REAL Large (Salesforce Research,Stanford University, 2016-11-04): 2.1e16 FLOP, confidence ConfidentNASv3 (CIFAR-10) (Google Brain, 2016-11-05): 2.2e21 FLOP, confidence LikelyNAS with base 8 and shared embeddings (Google Brain, 2016-11-05): 1.1e16 FLOP, confidence ConfidentBIDAF (University of Washington,Allen Institute for AI, 2016-11-05): 3.5e18 FLOP, confidence ConfidentResNeXt-101 (64×4d) (University of California San Diego,Facebook, 2016-11-16): 1.2e19 FLOP, confidence ConfidentPolyNet (Chinese University of Hong Kong (CUHK), 2016-11-17): 6.4e19 FLOP, confidence LikelyHR-ResNet101 (Carnegie Mellon University (CMU), 2016-12-13): 7.1e18 FLOP, confidence ConfidentEnhanceNet (Max Planck Institute for Intelligent Systems, 2016-12-23): 1.3e17 FLOP, confidence ConfidentDeepStack (University of Alberta,Charles University,Czech Technical University, 2017-01-06): 1.4e19 FLOP, confidence SpeculativeMoE-Multi (Jagiellonian University,Google Brain, 2017-01-23): 9.4e19 FLOP, confidence ConfidentTransformer (Google Research,Google Brain, 2017-06-12): 7.4e18 FLOP, confidence ConfidentDeepLoc (Technical University of Denmark,University of Copenhagen, 2017-07-07): 5.8e17 FLOP, confidence LikelyJFT (Google Research,Carnegie Mellon University (CMU), 2017-07-10): 8.4e20 FLOP, confidence ConfidentConvS2S (ensemble of 8 models) (Meta AI, 2017-07-25): 5.6e19 FLOP, confidence LikelyRetinaNet-R101 (Facebook AI Research, 2017-08-07): 2.1e18 FLOP, confidence ConfidentAWD-LSTM - 3-layer LSTM (tied) + continuous cache pointer (WT2) (Salesforce Research, 2017-08-07): 3.0e17 FLOP, confidence ConfidentOpenAI TI7 DOTA 1v1 (OpenAI, 2017-08-11): 6.0e20 FLOP, confidence ConfidentEI-REHN-1000D (Korea Advanced Institute of Science and Technology (KAIST), 2017-08-14): 1.1e16 FLOP, confidence ConfidentLibratus (Carnegie Mellon University (CMU), 2017-08-19): 5.5e20 FLOP, confidence LikelyGL-LWGC-AWD-MoS-LSTM + dynamic evaluation (WT2) (Ben-Gurion University of the Negev, 2017-08-29): 4.6e17 FLOP, confidence ConfidentPyramidNet (Korea Advanced Institute of Science and Technology (KAIST), 2017-09-06): 2.3e15 FLOP, confidence LikelyISS (Duke University,Microsoft, 2017-09-15): 3.4e15 FLOP, confidence ConfidentAWD-LSTM+WT+Cache+IOG (WT2) (NTT Communication Science Laboratories, 2017-09-26): 3.2e15 FLOP, confidence ConfidentAlphaGo Zero (DeepMind, 2017-10-18): 6.5e20 FLOP, confidence ConfidentAlphaGo Master (DeepMind, 2017-10-19): 3.4e20 FLOP, confidence LikelyFraternal dropout + AWD-LSTM 3-layer (WT2) (Jagiellonian University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de Montréal, 2017-10-31): 3.1e17 FLOP, confidence LikelyAWD-LSTM-MoS + dynamic evaluation (WT2, 2017) (Carnegie Mellon University (CMU), 2017-11-10): 3.4e18 FLOP, confidence LikelyAlphaZero (DeepMind, 2017-12-05): 1.1e20 FLOP, confidence LikelyQRNN (Salesforce Research, 2018-02-01): 6.9e17 FLOP, confidence LikelyELMo (University of Washington,Allen Institute for AI, 2018-02-01): 3.3e15 FLOP, confidence SpeculativeIMPALA (DeepMind, 2018-02-05): 1.7e20 FLOP, confidence Confident4 layer QRNN (h=2500) (Salesforce Research, 2018-03-22): 5.9e17 FLOP, confidence LikelyYOLOv3 (University of Washington, 2018-04-08): 1.3e19 FLOP, confidence LikelyResNeXt-101 32x48d (Facebook, 2018-05-02): 8.7e21 FLOP, confidence ConfidentDropout-LSTM+Noise(Bernoulli) (WT2) (Columbia University,New York University (NYU),Princeton University, 2018-05-03): 1.3e17 FLOP, confidence LikelyaLSTM(depth-2)+RecurrentPolicy (WT2) (University of Manchester,Alan Turing Institute, 2018-05-22): 7.3e16 FLOP, confidence ConfidentGPT-1 (OpenAI, 2018-06-01): 1.8e19 FLOP, confidence LikelyFTW (For The Win) (DeepMind, 2018-07-03): 3.5e19 FLOP, confidence SpeculativeBig-Little Net (speech) (IBM, 2018-07-10): 4.3e17 FLOP, confidence SpeculativeBig-Little Net (IBM, 2018-07-10): 2.5e17 FLOP, confidence LikelyBig Transformer for Back-Translation (Facebook AI Research,Google Brain, 2018-08-28): 4.8e20 FLOP, confidence Likely(ensemble): AWD-LSTM-DOC (fin) × 5 (WT2) (NTT Communication Science Laboratories,Tohoku University, 2018-08-30): 6.7e17 FLOP, confidence ConfidentTransformer + Simple Recurrent Unit (ASAPP,Cornell University,Google,Princeton University, 2018-09-17): 1.1e19 FLOP, confidence ConfidentLSTM+NeuralCache (KU Leuven,ESAT - PSI,Apple, 2018-09-24): 9.8e14 FLOP, confidence LikelyTransformer (Adaptive Input Embeddings) WT103 (Facebook AI Research, 2018-09-28): 4.5e19 FLOP, confidence ConfidentBERT-Large (Google, 2018-10-11): 2.9e20 FLOP, confidence ConfidentTrellisNet (Carnegie Mellon University (CMU),Bosch Center for Artificial Intelligence,Intel Labs, 2018-10-15): 2.8e18 FLOP, confidence ConfidentMesh-TensorFlow Transformer 4.9B (language) (Google Brain, 2018-11-05): 1.6e20 FLOP, confidence ConfidentMesh-TensorFlow Transformer 2.9B (translation) (Google Brain, 2018-11-05): 6.8e19 FLOP, confidence LikelyFine-tuned-AWD-LSTM-DOC (fin) (Samsung R&D Institute Russia, 2018-11-12): 5.2e16 FLOP, confidence ConfidentMulti-cell LSTM (University of Hyderabad, 2018-11-15): 2.0e15 FLOP, confidence LikelyStyleGAN (Nvidia, 2018-12-12): 3.9e16 FLOP, confidence ConfidentTransformer-XL (257M) (Carnegie Mellon University (CMU),Google Brain, 2019-01-09): 3.8e20 FLOP, confidence SpeculativeHanabi 4 player (DeepMind,University of Oxford,Carnegie Mellon University (CMU),Google Brain, 2019-02-01): 4.3e18 FLOP, confidence ConfidentGPT-2 (1.5B) (OpenAI, 2019-02-14): 1.9e21 FLOP, confidence SpeculativeKataGo (Jane Street, 2019-02-27): 2.3e19 FLOP, confidence SpeculativeSciBERT (Allen Institute for AI, 2019-03-26): 8.9e19 FLOP, confidence ConfidentCross-lingual alignment (Tel Aviv University,Massachusetts Institute of Technology (MIT), 2019-04-04): 2.6e18 FLOP, confidence SpeculativeWeNet (Penn Treebank) (Amazon, 2019-04-08): 7.3e17 FLOP, confidence LikelyBERT-Large-CAS (PTB+WT2+WT103) (Amazon, 2019-04-20): 1.5e20 FLOP, confidence LikelyMuseNet (OpenAI, 2019-04-25): 2.2e20 FLOP, confidence LikelyAWD-LSTM-DRILL + dynamic evaluation† (WT2) (IDIAP, 2019-05-14): 4.1e17 FLOP, confidence LikelyDLRM-2020 (Facebook AI, 2019-05-31): 4.0e18 FLOP, confidence ConfidentXLNet (Carnegie Mellon University (CMU),Google Brain, 2019-06-01): 6.2e21 FLOP, confidence ConfidentTransformer-XL Large + Phrase Induction (Massachusetts Institute of Technology (MIT),University of Illinois Urbana-Champaign (UIUC), 2019-06-04): 3.8e20 FLOP, confidence SpeculativeAWD-LSTM + MoS + Partial Shuffled (University of Texas at Austin, 2019-06-10): 3.1e17 FLOP, confidence ConfidentRoBERTa Large (Facebook,University of Washington, 2019-07-01): 8.5e21 FLOP, confidence ConfidentPluribus (Facebook AI Research, 2019-07-11): 6.6e16 FLOP, confidence LikelytrRosetta (Nankai University,University of Washington,Tianjin University,Harvard University, 2019-08-22): 3.8e19 FLOP, confidence ConfidentUDSMProt (Fraunhofer Heinrich Hertz Institute, 2019-09-04): 6.4e17 FLOP, confidence LikelyMegatron-LM (8.3B) (Nvidia, 2019-09-17): 9.1e21 FLOP, confidence LikelyMegatron-LM (1.2B) (Nvidia, 2019-09-17): 1.1e21 FLOP, confidence ConfidentMegatron-BERT (Nvidia, 2019-09-17): 2.2e22 FLOP, confidence ConfidentDistilBERT (Hugging Face, 2019-10-02): 1.2e19 FLOP, confidence ConfidentAlphaX-1 (Facebook AI Research,Brown University, 2019-10-02): 8.9e17 FLOP, confidence ConfidentT5-11B (Google, 2019-10-23): 3.3e22 FLOP, confidence ConfidentT5-3B (Google, 2019-10-23): 9.0e21 FLOP, confidence ConfidentAlphaStar (DeepMind, 2019-10-30): 1.1e23 FLOP, confidence ConfidentBase LM + kNN LM + Continuous Cache (Stanford University,Facebook AI Research, 2019-11-01): 3.1e19 FLOP, confidence LikelyXLM-RoBERTa (Facebook AI, 2019-11-05): 2.1e22 FLOP, confidence ConfidentSandwich Transformer (Allen Institute for AI,Facebook AI Research, 2019-11-10): 2.4e19 FLOP, confidence SpeculativeCamemBERT (Facebook,INRIA,Sorbonne University, 2019-11-10): 8.3e20 FLOP, confidence ConfidentNoisy Student (L2) (Carnegie Mellon University (CMU),Google, 2019-11-11): 2.6e22 FLOP, confidence ConfidentMuZero (DeepMind, 2019-11-19): 4.8e19 FLOP, confidence SpeculativeTransformer-XL DeFINE (141M) (University of Washington,Allen Institute for AI, 2019-11-27): 1.7e18 FLOP, confidence SpeculativeMMLSTM (WT-2) (Beijing University of Posts and Telecommunications,University of West London, 2019-12-05): 1.9e17 FLOP, confidence LikelyMMLSTM (PTB) (Beijing University of Posts and Telecommunications,University of West London, 2019-12-05): 5.8e16 FLOP, confidence LikelyOpenAI Five Rerun (OpenAI, 2019-12-13): 1.3e22 FLOP, confidence ConfidentOpenAI Five (OpenAI, 2019-12-13): 6.7e22 FLOP, confidence ConfidentDD-PPO (Georgia Institute of Technology,Facebook AI Research,Oregon State University,Simon Fraser University, 2019-12-19): 7.8e20 FLOP, confidence LikelyAlphaFold (DeepMind, 2020-01-15): 1.0e20 FLOP, confidence SpeculativeContextNet + Noisy Student (Google, 2020-01-19): 8.2e21 FLOP, confidence ConfidentMeena (Google Brain, 2020-01-28): 1.1e23 FLOP, confidence ConfidentTaLK Convolution (Carleton University, 2020-02-08): 2.7e19 FLOP, confidence LikelyALBERT-xxlarge (Toyota Technological Institute at Chicago,Google, 2020-02-09): 2.4e21 FLOP, confidence SpeculativeTuring-NLG (Microsoft, 2020-02-13): 1.6e22 FLOP, confidence LikelyFFN SwiGLU (Google, 2020-02-14): 3.4e19 FLOP, confidence ConfidentFeedback Transformer (LORIA,University of Lorraine,Facebook AI Research, 2020-02-21): 7.7e18 FLOP, confidence SpeculativeTransformerXL + spectrum control (University of California Los Angeles (UCLA),JD.com, 2020-03-11): 2.6e19 FLOP, confidence SpeculativeTensor-Transformer(1core)+PN (WT103) (University of California (UC) Berkeley, 2020-03-17): 1.6e18 FLOP, confidence ConfidentELECTRA (Stanford University,Google,Google Brain, 2020-03-23): 3.1e21 FLOP, confidence LikelyMetNet (Google, 2020-03-24): 9.5e18 FLOP, confidence SpeculativeOnce for All (MIT-IBM Watson AI Lab,Massachusetts Institute of Technology (MIT),IBM, 2020-04-29): 6.2e20 FLOP, confidence ConfidentUnifiedQA (Allen Institute for AI,University of Washington, 2020-05-02): 1.6e19 FLOP, confidence ConfidentDETR (Facebook, 2020-05-26): 4.0e20 FLOP, confidence ConfidentGPT-3 175B (davinci) (OpenAI, 2020-05-28): 3.1e23 FLOP, confidence ConfidentGShard (dense) (Google, 2020-06-30): 4.8e22 FLOP, confidence ConfidentDeLighT (University of Washington,Allen Institute for AI,Facebook AI Research, 2020-08-03): 3.8e18 FLOP, confidence LikelyERNIE-GEN (large) (Baidu, 2020-08-06): 2.0e20 FLOP, confidence SpeculativeProBERTa (University of Illinois Urbana-Champaign (UIUC),Reed College, 2020-09-01): 9.7e18 FLOP, confidence ConfidentLUKE (University of Washington,National Institute of Informatics, 2020-10-02): 1.8e22 FLOP, confidence LikelymT5-XXL (Google,Google Research, 2020-10-20): 8.2e22 FLOP, confidence ConfidentConformer + Wav2vec 2.0 + Noisy Student (Google,Google Research,Google Brain, 2020-10-20): 7.6e21 FLOP, confidence ConfidentGerman ELECTRA Large (deepset,Bayerische Staatsbibliothek Muenchen, 2020-10-21): 1.4e21 FLOP, confidence Confidentwave2vec 2.0 LARGE (Facebook, 2020-10-22): 3.9e21 FLOP, confidence ConfidentViT-Huge/14 (Google Brain,Google Research, 2020-10-22): 4.3e21 FLOP, confidence ConfidentKEPLER (Tsinghua University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),HEC,CIFAR AI Research,Princeton University,University of Montreal / Université de Montréal, 2020-11-23): 1.7e21 FLOP, confidence ConfidentAlphaFold 2 (DeepMind, 2020-11-30): 3.0e21 FLOP, confidence LikelyCPM-Large (Tsinghua University,Beijing Academy of Artificial Intelligence / BAAI, 2020-12-01): 2.6e20 FLOP, confidence ConfidentESM1b (Facebook AI Research,New York University (NYU), 2020-12-15): 5.1e21 FLOP, confidence ConfidentDensePhrases (Korea University,Princeton University, 2020-12-23): 2.1e18 FLOP, confidence SpeculativeCT-MoS (WT2) (Google,National Tsing Hua University, 2020-12-25): 5.4e17 FLOP, confidence ConfidentERNIE-Doc (247M) (Baidu, 2020-12-31): 3.0e19 FLOP, confidence ConfidentDALL-E (OpenAI, 2021-01-05): 4.7e22 FLOP, confidence LikelyCLIP (ViT L/14@336px) (OpenAI, 2021-01-05): 1.0e22 FLOP, confidence ConfidentSwitch (Google, 2021-01-11): 8.2e22 FLOP, confidence ConfidentDeiT-B (Meta AI,Sorbonne University, 2021-01-15): 7.9e19 FLOP, confidence ConfidentDLWP (University of Washington,Microsoft Research, 2021-02-09): 5.7e18 FLOP, confidence ConfidentMSA Transformer (Facebook AI Research,University of California (UC) Berkeley,New York University (NYU), 2021-02-13): 5.5e21 FLOP, confidence LikelySRU++ Large (ASAPP, 2021-02-24): 2.1e19 FLOP, confidence ConfidentMeta Pseudo Labels (Google Brain,Google AI, 2021-03-01): 4.8e22 FLOP, confidence LikelyM6-T (Alibaba, 2021-03-05): 5.5e21 FLOP, confidence LikelyGenerative BST (Facebook AI Research, 2021-03-05): 1.4e22 FLOP, confidence ConfidentPLUG (Alibaba, 2021-04-19): 3.6e22 FLOP, confidence ConfidentProtT5-XL-U50 (Technical University of Munich,Med AI Technology,Nvidia,Oak Ridge National Laboratory,Google,Seoul National University, 2021-05-04): 1.9e22 FLOP, confidence ConfidentProtBERT-BFD (Technical University of Munich,Nvidia,Seoul National University,Google,Oak Ridge National Laboratory,Med AI Technology, 2021-05-04): 3.9e22 FLOP, confidence ConfidentADM (OpenAI, 2021-05-11): 6.2e21 FLOP, confidence ConfidentMedBERT (Peng Cheng Laboratory,University of Texas at Houston, 2021-05-20): 9.5e18 FLOP, confidence LikelyTransformer local-attention (NesT-B) (Google Cloud,Google Research, 2021-05-26): 2.4e19 FLOP, confidence ConfidentCogView (Tsinghua University,Alibaba DAMO Academy, 2021-05-26): 2.7e22 FLOP, confidence LikelyByT5-XXL (Google,Google Research, 2021-05-28): 8.1e22 FLOP, confidence LikelyViT-G/14 (Google Brain,Google Research, 2021-06-08): 5.8e22 FLOP, confidence ConfidentEMDR (Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),McGill University,DeepMind, 2021-06-09): 1.9e21 FLOP, confidence ConfidentCoAtNet (Google,Google Research,Google Brain, 2021-06-09): 4.3e22 FLOP, confidence ConfidentDeBERTa (Microsoft, 2021-06-10): 2.6e22 FLOP, confidence ConfidentDenoising Diffusion Probabilistic Models (LSUN Bedroom) (University of California (UC) Berkeley, 2021-06-11): 7.8e19 FLOP, confidence ConfidentALIGN (Google Research, 2021-06-11): 2.6e22 FLOP, confidence ConfidentStyleGAN3-T (Nvidia,Aalto University, 2021-06-21): 1.7e21 FLOP, confidence ConfidentStyleGAN3-R (Nvidia,Aalto University, 2021-06-21): 2.4e21 FLOP, confidence ConfidentEfficientNetV2-XL (Google,Google Brain, 2021-06-23): 9.6e19 FLOP, confidence ConfidentFold2Seq (IBM,Texas A&M, 2021-06-24): 1.4e17 FLOP, confidence SpeculativeAdaptive Input Transformer + RD (Microsoft Research Asia,Soochow University, 2021-06-28): 8.6e19 FLOP, confidence LikelyERNIE 3.0 (Baidu, 2021-07-05): 2.3e22 FLOP, confidence ConfidentCodex (OpenAI, 2021-07-07): 7.3e22 FLOP, confidence LikelyHuBERT (Facebook AI Research, 2021-07-27): 5.5e21 FLOP, confidence SpeculativeGOAT (DeepMind, 2021-07-27): 2.4e22 FLOP, confidence SpeculativeSEER (Facebook AI Research,INRIA, 2021-07-29): 1.8e22 FLOP, confidence ConfidentYOLOX-X (Megvii Inc, 2021-08-06): 6.3e20 FLOP, confidence LikelyZidong Taichu (Chinese Academy of Sciences,Wuhan AI Computing Center, 2021-08-11): 8.0e20 FLOP, confidence ConfidentJurassic-1-Jumbo (AI21 Labs, 2021-08-11): 3.7e23 FLOP, confidence ConfidentDNABERT (Northeastern University, 2021-08-15): 1.1e20 FLOP, confidence ConfidentXLMR-XXL (Facebook AI Research, 2021-08-17): 3.4e22 FLOP, confidence ConfidentFLAN 137B (Google Research, 2021-09-03): 2.0e24 FLOP, confidence ConfidentPermuteFormer (Peking University, 2021-09-06): 2.8e18 FLOP, confidence SpeculativeHyperCLOVA 204B (NAVER, 2021-09-10): 2.0e23 FLOP, confidence SpeculativePLATO-XL (Baidu, 2021-09-20): 9.9e21 FLOP, confidence ConfidentTuring ULRv5 (Microsoft, 2021-09-28): 2.9e22 FLOP, confidence ConfidentAlphaFold-Multimer (Google DeepMind,DeepMind, 2021-10-04): 4.3e21 FLOP, confidence ConfidentMegatron-Turing NLG 530B (Microsoft,Nvidia, 2021-10-11): 8.6e23 FLOP, confidence ConfidentYuan 1.0 (Inspur, 2021-10-12): 3.5e23 FLOP, confidence Confidentbase LM+GNN+kNN (Shannon.AI,Nanjing University,Nanyang Technological University,Zhejiang University (ZJU), 2021-10-17): 5.3e19 FLOP, confidence ConfidentS4 (Stanford University, 2021-10-31): 7.8e19 FLOP, confidence LikelyProjected GAN (Heidelberg University, 2021-11-01): 1.1e19 FLOP, confidence ConfidentCodeT5-base (Salesforce,Nanyang Technological University, 2021-11-01): 1.6e21 FLOP, confidence LikelyMasked Autoencoders ViT-H (Facebook AI Research, 2021-11-11): 4.6e20 FLOP, confidence SpeculativeSwin Transformer V2 (SwinV2-G) (Microsoft Research Asia, 2021-11-18): 1.1e21 FLOP, confidence ConfidentBASIC-L (Google, 2021-11-19): 4.1e22 FLOP, confidence LikelyFlorence (Microsoft, 2021-11-22): 4.8e22 FLOP, confidence ConfidentNÜWA (Microsoft Research,Peking University, 2021-11-24): 7.2e21 FLOP, confidence ConfidentStudent of Games (DeepMind, 2021-12-06): 3.7e22 FLOP, confidence SpeculativeGopher (280B) (DeepMind, 2021-12-08): 6.3e23 FLOP, confidence ConfidentGLaM (Google, 2021-12-13): 3.6e23 FLOP, confidence ConfidentContriever (Meta AI,University College London (UCL),PSL University,Université Grenoble Alpes, 2021-12-16): 1.6e20 FLOP, confidence LikelyXGLM-7.5B (Meta AI,Facebook AI Research, 2021-12-20): 2.3e22 FLOP, confidence ConfidentERNIE 3.0 Titan (Baidu,Peng Cheng Laboratory, 2021-12-23): 1.0e24 FLOP, confidence ConfidentDetic (Meta AI,University of Texas at Austin, 2022-01-07): 2.3e19 FLOP, confidence SpeculativeInstructGPT 175B (OpenAI, 2022-01-27): 3.2e23 FLOP, confidence ConfidentAlphaCode (DeepMind, 2022-02-02): 2.4e23 FLOP, confidence ConfidentRETRO-7B (DeepMind, 2022-02-07): 1.7e22 FLOP, confidence ConfidentGPT-NeoX-20B (EleutherAI, 2022-02-09): 9.3e22 FLOP, confidence ConfidentProteinBERT (Hebrew University of Jerusalem,Ben-Gurion University of the Negev,Deep Trading, 2022-02-10): 6.5e19 FLOP, confidence ConfidentLaMDA (Google, 2022-02-10): 3.6e23 FLOP, confidence ConfidentST-MoE (Google,Google Brain,Google Research, 2022-02-17): 2.9e23 FLOP, confidence LikelyFourCastNet (Nvidia,NERSC, Lawrence Berkeley National Laboratory,University of Michigan,Rice University,California Institute of Technology,Purdue University, 2022-02-22): 3.5e20 FLOP, confidence ConfidentPolyCoder (Carnegie Mellon University (CMU), 2022-02-26): 1.1e21 FLOP, confidence LikelyStatement Curriculum Learning (OpenAI, 2022-03-02): 1.8e22 FLOP, confidence LikelyViT-G (model soup) (University of Washington,Columbia University,Google,Meta AI,Tel Aviv University, 2022-03-10): 3.4e21 FLOP, confidence ConfidentGPT-3.5 (davinci-002) (OpenAI, 2022-03-15): 2.6e24 FLOP, confidence SpeculativeSegatron-XL large, M=384 + HCP (Microsoft Research,University of Waterloo, 2022-03-21): 2.6e19 FLOP, confidence ConfidentMake-A-Scene (Meta AI, 2022-03-24): 6.4e21 FLOP, confidence LikelyChinchilla (DeepMind, 2022-03-29): 5.8e23 FLOP, confidence ConfidentPaLM (540B) (Google Research, 2022-04-04): 2.5e24 FLOP, confidence ConfidentDALL·E 2 (OpenAI, 2022-04-06): 3.4e23 FLOP, confidence SpeculativeBERT-RBP (Waseda University, 2022-04-07): 1.4e20 FLOP, confidence ConfidentStable Diffusion (LDM-KL-8-G) (Runway,Ludwig Maximilian University of Munich,Heidelberg University, 2022-04-13): 5.0e22 FLOP, confidence ConfidentSparse all-MLP (Meta AI, 2022-04-14): 5.3e20 FLOP, confidence ConfidentFlamingo (DeepMind, 2022-04-29): 2.2e23 FLOP, confidence ConfidentOPT-175B (Meta AI, 2022-05-02): 4.3e23 FLOP, confidence ConfidentUL2 (Google Research,Google Brain, 2022-05-10): 1.2e23 FLOP, confidence ConfidentGato (DeepMind, 2022-05-12): 4.0e21 FLOP, confidence ConfidentImagen (Google Brain, 2022-05-23): 1.5e22 FLOP, confidence LikelyTranception (University of Oxford,Harvard Medical School,Cohere, 2022-05-27): 7.2e21 FLOP, confidence ConfidentGPT-2 Medium (FlashAttention) (Stanford University,University at Buffalo, 2022-05-27): 8.9e20 FLOP, confidence ConfidentDITTO (Tsinghua University,Apple,Westlake University,Chinese University of Hong Kong (CUHK), 2022-06-06): 3.3e18 FLOP, confidence ConfidentCoCa (Google Research, 2022-06-14): 7.3e22 FLOP, confidence ConfidentParti (Google Research, 2022-06-22): 5.1e23 FLOP, confidence ConfidentProGen2-xlarge (Salesforce Research,Columbia University,Johns Hopkins University, 2022-06-27): 1.4e22 FLOP, confidence ConfidentMinerva (540B) (Google, 2022-06-29): 2.7e24 FLOP, confidence ConfidentCodeT5-large (Salesforce, 2022-07-05): 2.7e21 FLOP, confidence LikelyNLLB (Meta AI, 2022-07-06): 1.8e22 FLOP, confidence ConfidentBLOOM-176B (Hugging Face,BigScience, 2022-07-11): 3.7e23 FLOP, confidence ConfidentESM2-15B (Meta AI,New York University (NYU),Stanford University,Massachusetts Institute of Technology (MIT), 2022-07-21): 7.4e22 FLOP, confidence ConfidentOmegaPLM (Massachusetts Institute of Technology (MIT),Westlake University, 2022-07-22): 1.0e22 FLOP, confidence ConfidentAlexaTM 20B (Amazon, 2022-08-02): 2.0e23 FLOP, confidence ConfidentGLM-130B (Tsinghua University, 2022-08-04): 3.5e23 FLOP, confidence ConfidentBlenderBot 3 (McGill University,Meta AI,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms), 2022-08-10): 4.3e23 FLOP, confidence LikelyBEIT-3 (Microsoft, 2022-08-22): 7.0e19 FLOP, confidence LikelyPaLI (Google, 2022-09-14): 1.7e23 FLOP, confidence LikelyWhisper (OpenAI, 2022-09-21): 4.2e21 FLOP, confidence LikelyDiffDock (Massachusetts Institute of Technology (MIT), 2022-10-04): 7.2e19 FLOP, confidence LikelyAlphaTensor (DeepMind, 2022-10-05): 7.1e20 FLOP, confidence ConfidentGenSLM (University of Chicago,Nvidia,Harvard University,Cerebras Systems,Technical University of Munich,California Institute of Technology, 2022-10-11): 1.4e21 FLOP, confidence ConfidentU-PaLM (540B) (Google, 2022-10-20): 2.5e24 FLOP, confidence ConfidentFlan-PaLM 540B (Google, 2022-10-20): 2.5e24 FLOP, confidence ConfidenteDiff-I (Nvidia, 2022-11-02): 5.5e19 FLOP, confidence LikelyMogrifier RLSTM (WT2) (DeepMind, 2022-11-03): 1.4e17 FLOP, confidence ConfidentInternImage (Shanghai AI Lab,Tsinghua University,Nanjing University,SenseTime,Chinese University of Hong Kong (CUHK), 2022-11-10): 2.4e21 FLOP, confidence ConfidentEVA-01 (Beijing Academy of Artificial Intelligence / BAAI,Huazhong University of Science and Technology,Zhejiang University (ZJU),Beijing Institute of Technology, 2022-11-14): 1.5e22 FLOP, confidence ConfidentGalactica (Meta AI, 2022-11-16): 3.2e23 FLOP, confidence LikelyFusion in Encoder (Samsung, 2022-11-18): 1.3e20 FLOP, confidence LikelyAR-LDM (Alibaba,University of Waterloo,Vector Institute, 2022-11-20): 5.1e20 FLOP, confidence ConfidentDiscriminator Guidance (Korea Advanced Institute of Science and Technology (KAIST),NAVER, 2022-11-28): 2.2e20 FLOP, confidence ConfidentVega v2 (Wuhan University,JD Explore Academy,Shanghai AI Lab,Nanyang Technological University,Washington University in St Louis,Chongqing University of Posts and Telecommunications,University of Sydney, 2022-12-04): 7.8e22 FLOP, confidence ConfidentCaLM (University of Oxford, 2022-12-19): 2.9e19 FLOP, confidence LikelyHybrid H3-2.7B (Stanford University,University at Buffalo, 2022-12-28): 6.5e21 FLOP, confidence LikelyVALL-E (Microsoft, 2023-01-05): 1.0e19 FLOP, confidence SpeculativeDreamerV3 (DeepMind,University of Toronto, 2023-01-10): 2.2e20 FLOP, confidence LikelyNucleotide Transformer (Nvidia,Technical University of Munich,InstaDeep, 2023-01-15): 8.1e21 FLOP, confidence LikelyAnkh_large (Technical University of Munich,Columbia University, 2023-01-16): 6.5e21 FLOP, confidence ConfidentDDPM-IP (CelebA) (Utrecht University, 2023-01-27): 3.5e20 FLOP, confidence LikelyBLIP-2 (Q-Former) (Salesforce Research, 2023-01-30): 1.2e21 FLOP, confidence ConfidentViT-22B (Google, 2023-02-10): 1.9e23 FLOP, confidence ConfidentLLaMA-65B (Meta AI, 2023-02-24): 5.5e23 FLOP, confidence ConfidentDiT-XL/2 (New York University (NYU),University of California (UC) Berkeley, 2023-03-02): 6.0e20 FLOP, confidence ConfidentAudioGen (Meta AI,Hebrew University of Jerusalem, 2023-03-05): 9.5e21 FLOP, confidence LikelyGPT-4 (Mar 2023) (OpenAI, 2023-03-15): 2.1e25 FLOP, confidence LikelyFalcon-40B (Technology Innovation Institute, 2023-03-15): 2.4e23 FLOP, confidence ConfidentPanGu-Σ (Huawei Noah's Ark Lab, 2023-03-20): 4.7e23 FLOP, confidence ConfidentSigLIP 400M (Google DeepMind, 2023-03-27): 4.9e21 FLOP, confidence ConfidentVideoMAE V2 (Nanjing University,Shenzhen Institute of Advanced Technology,Shanghai AI Lab, 2023-03-29): 9.7e21 FLOP, confidence ConfidentBloombergGPT (Bloomberg,Johns Hopkins University, 2023-03-30): 2.4e23 FLOP, confidence ConfidentSegment Anything Model (Meta AI, 2023-04-05): 7.8e21 FLOP, confidence ConfidentIncoder-6.7B (Facebook AI Research,University of Washington,University of California (UC) Berkeley,Carnegie Mellon University (CMU),Toyota Technological Institute at Chicago, 2023-04-09): 3.0e21 FLOP, confidence ConfidentDINOv2 (Facebook AI Research,INRIA, 2023-04-14): 7.4e21 FLOP, confidence ConfidentLLaVA (University of Wisconsin Madison,Microsoft Research,Columbia University, 2023-04-17): 7.8e22 FLOP, confidence ConfidentStarCoder (Hugging Face,ServiceNow,Northeastern University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Carnegie Mellon University (CMU),Johns Hopkins University,Leipzig University,ScaDS.AI,Queen Mary University of London,Roblox,Sea AI Lab,Technion - Israel Institute of Technology,Monash University,CSIRO,Data61,McGill University,Saama,University of British Columbia (UBC),Massachusetts Institute of Technology (MIT),Technical University of Munich,IBM,University of Vermont,UnfoldML,SAP,University of Notre Dame,Columbia University,New York University (NYU),University of Allahabad,Discover Dollar,Toloka,Telefonica,Stanford University,Weizmann Institute of Science,Alan Turing Institute,Wellesley College,EleutherAI,Forschungszentrum Julich, 2023-05-09): 8.5e22 FLOP, confidence ConfidentPaLM 2 (Google, 2023-05-10): 7.3e24 FLOP, confidence LikelyInstructBLIP (Salesforce Research,Hong Kong University of Science and Technology (HKUST),Nanyang Technological University, 2023-05-11): 1.9e20 FLOP, confidence ConfidentONE-PEACE (Alibaba,Huazhong University of Science and Technology, 2023-05-18): 1.8e20 FLOP, confidence SpeculativePaLI-X (Google Research, 2023-05-29): 5.6e23 FLOP, confidence LikelyGPT-4 (Jun 2023) (OpenAI, 2023-06-13): 2.1e25 FLOP, confidence LikelyHyenaDNA (Stanford University,Harvard University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de Montréal, 2023-06-27): 1.8e21 FLOP, confidence ConfidentPangu-Weather (Huawei, 2023-07-05): 4.0e22 FLOP, confidence ConfidentxTrimoPGLM -100B (Tsinghua University,BioMap Research, 2023-07-06): 6.2e23 FLOP, confidence ConfidentInternLM (Shanghai AI Lab,SenseTime, 2023-07-06): 10.0e23 FLOP, confidence ConfidentClaude 2 (Anthropic, 2023-07-11): 3.9e24 FLOP, confidence SpeculativeLlama 2-70B (Meta AI, 2023-07-18): 8.1e23 FLOP, confidence ConfidentLlama 2-7B (Meta AI, 2023-07-18): 8.4e22 FLOP, confidence ConfidentAudioLM (Google Research, 2023-07-26): 3.9e18 FLOP, confidence SpeculativeGGNN (Westlake University,Tsinghua University,Toyota Technological Institute at Chicago, 2023-08-05): 7.6e21 FLOP, confidence ConfidentPeptideBERT (Carnegie Mellon University (CMU), 2023-08-28): 4.9e16 FLOP, confidence ConfidentJais (Cerebras Systems,Mohamed bin Zayed University of Artificial Intelligence (MBZUAI),Inception G42, 2023-08-29): 4.9e22 FLOP, confidence ConfidentSwift (Intel Labs, 2023-08-30): 5.3e16 FLOP, confidence LikelyFalcon-180B (Technology Innovation Institute, 2023-09-06): 3.8e24 FLOP, confidence ConfidentAmazon Titan (Amazon, 2023-09-28): 4.8e24 FLOP, confidence LikelyFinGPT-13B (University of California Los Angeles (UCLA),Columbia University,New York University (NYU), 2023-10-07): 1.6e23 FLOP, confidence LikelyRoseTTAFold All-Atom (RFAA) (University of Washington,Seoul National University,University of Sheffield, 2023-10-09): 2.1e20 FLOP, confidence ConfidentCODEFUSION (Python) (Microsoft,Microsoft Research, 2023-10-26): 7.9e18 FLOP, confidence ConfidentChatGLM3-6B (Z.ai (Zhipu AI), 2023-10-27): 5.0e22 FLOP, confidence SpeculativeSkywork-13B (Kunlun Inc., 2023-10-30): 2.5e23 FLOP, confidence ConfidentYi-34B (01.AI, 2023-11-02): 6.1e23 FLOP, confidence ConfidentGrok-1 (xAI, 2023-11-04): 2.9e24 FLOP, confidence LikelyLLaVA 1.5 (University of Wisconsin Madison,Microsoft Research, 2023-11-05): 7.8e22 FLOP, confidence ConfidentCogVLM-17B (Tsinghua University,Z.ai (Zhipu AI),Beihang University, 2023-11-06): 6.3e22 FLOP, confidence ConfidentRoFormer (Zhuiyi Technology, 2023-11-08): 2.2e18 FLOP, confidence ConfidentMultiBand Diffusion (Meta AI,Hebrew University of Jerusalem,LORIA, 2023-11-08): 2.6e19 FLOP, confidence ConfidentVolcano 13B (Korea University,Korea Advanced Institute of Science and Technology (KAIST),LG, 2023-11-13): 4.6e22 FLOP, confidence LikelySPHINX (Llama 2 13B) (Shanghai AI Lab,Chinese University of Hong Kong (CUHK),ShanghaiTech University, 2023-11-13): 3.0e22 FLOP, confidence LikelyGraphCast (Google DeepMind, 2023-11-14): 2.1e22 FLOP, confidence SpeculativeNemotron-3-8B (Nvidia, 2023-11-15): 1.8e23 FLOP, confidence ConfidentInflection-2 (Inflection AI, 2023-11-22): 1.0e25 FLOP, confidence ConfidentQwen-72B (Alibaba, 2023-11-30): 1.3e24 FLOP, confidence ConfidentGemini 1.0 Ultra (Google DeepMind, 2023-12-06): 5.0e25 FLOP, confidence SpeculativeLlama Guard (Meta AI, 2023-12-07): 1.6e23 FLOP, confidence ConfidentMixtral 8x7B (Mistral AI, 2023-12-11): 7.7e23 FLOP, confidence SpeculativeVILA-13B (Nvidia,Massachusetts Institute of Technology (MIT), 2023-12-12): 2.3e21 FLOP, confidence ConfidentFunSearch (Google DeepMind, 2023-12-14): 3.9e23 FLOP, confidence SpeculativeCogAgent (Tsinghua University,Z.ai (Zhipu AI), 2023-12-14): 6.7e22 FLOP, confidence Likelynekomata-14b (rinna, 2023-12-21): 2.6e23 FLOP, confidence ConfidentGQA-8-XXL (Google Research, 2023-12-23): 3.5e22 FLOP, confidence ConfidentQwen1.5-72B (Alibaba, 2024-02-04): 1.3e24 FLOP, confidence ConfidentStable Diffusion 3 (Stability AI, 2024-02-22): 5.0e22 FLOP, confidence ConfidentMegaScale (Production) (ByteDance,Peking University, 2024-02-23): 3.9e24 FLOP, confidence SpeculativeAramco Metabrain AI (Saudi Aramco, 2024-03-04): 1.0e25 FLOP, confidence LikelyInflection-2.5 (Inflection AI, 2024-03-07): 8.0e24 FLOP, confidence LikelyMM1-30B (Apple, 2024-03-14): 4.9e23 FLOP, confidence LikelyDBRX (Databricks, 2024-03-27): 2.6e24 FLOP, confidence ConfidentReka Core (Reka AI, 2024-04-15): 8.4e24 FLOP, confidence SpeculativeLlama 3-70B (Meta AI, 2024-04-18): 7.9e24 FLOP, confidence ConfidentGenCast (Google DeepMind, 2024-05-01): 8.2e20 FLOP, confidence ConfidentVILA1.5-13B (Nvidia,Massachusetts Institute of Technology (MIT), 2024-05-03): 2.3e21 FLOP, confidence ConfidentAlphaFold 3 (Google DeepMind,Isomorphic Labs, 2024-05-08): 4.1e22 FLOP, confidence ConfidentYi-Large (01.AI, 2024-05-13): 1.8e24 FLOP, confidence SpeculativeOcto-Base (University of California (UC) Berkeley,Stanford University,Carnegie Mellon University (CMU),DeepMind, 2024-05-20): 5.8e20 FLOP, confidence ConfidentALLaM adapted 70B (Saudi Data and Artificial Intelligence Authority, 2024-05-21): 1.1e24 FLOP, confidence ConfidentQwen2-72B (Alibaba, 2024-06-07): 3.0e24 FLOP, confidence ConfidentOpenVLA (Stanford University,University of California (UC) Berkeley,Toyota Research Institute,Google DeepMind,Massachusetts Institute of Technology (MIT),Physical Intelligence, 2024-06-13): 1.1e23 FLOP, confidence ConfidentNemotron-4 340B (Nvidia, 2024-06-14): 1.8e25 FLOP, confidence ConfidentDeepSeek-Coder-V2 236B (DeepSeek, 2024-06-17): 1.3e24 FLOP, confidence ConfidentClaude 3.5 Sonnet (Anthropic, 2024-06-20): 2.7e25 FLOP, confidence SpeculativeESM3 (98B) (EvolutionaryScale,University of California (UC) Berkeley, 2024-06-25): 1.1e24 FLOP, confidence ConfidentLlama 3.1-405B (Meta AI, 2024-07-23): 3.8e25 FLOP, confidence ConfidentAFM-server (Apple, 2024-07-29): 4.3e24 FLOP, confidence LikelyAFM-on-device (Apple, 2024-07-29): 4.5e23 FLOP, confidence ConfidentLLaVA-OV-72B (ByteDance,Nanyang Technological University,Chinese University of Hong Kong (CUHK),Hong Kong University of Science and Technology (HKUST), 2024-08-06): 3.0e24 FLOP, confidence ConfidentGrok-2 (xAI, 2024-08-13): 3.0e25 FLOP, confidence ConfidentDeepSeek-V2.5 (DeepSeek, 2024-09-06): 1.8e24 FLOP, confidence ConfidentQwen2.5-32B (Alibaba, 2024-09-17): 3.5e24 FLOP, confidence ConfidentQwen2.5-72B (Alibaba, 2024-09-19): 7.8e24 FLOP, confidence ConfidentQwen2.5 Instruct (72B) (Alibaba, 2024-09-19): 7.9e24 FLOP, confidence ConfidentTelechat2-115B (China Telecom, 2024-09-20): 6.9e24 FLOP, confidence ConfidentLlama 3.2 11B (Meta AI, 2024-09-24): 5.8e23 FLOP, confidence ConfidentMovie Gen Video (Meta AI, 2024-10-04): 1.6e24 FLOP, confidence ConfidentRDT-1B (Tsinghua University, 2024-10-10): 4.1e22 FLOP, confidence LikelyLlama-3.1-Nemotron-70B-Instruct (Nvidia,Meta AI, 2024-10-12): 7.9e24 FLOP, confidence ConfidentCHAI-1 (Chai discovery, 2024-10-15): 7.8e21 FLOP, confidence ConfidentYi-Lightning (01.AI, 2024-10-16): 1.5e24 FLOP, confidence ConfidentNVLM-X 72B (Nvidia, 2024-10-22): 3.0e24 FLOP, confidence LikelyNVLM-H 72B (Nvidia, 2024-10-22): 3.0e24 FLOP, confidence LikelyNVLM-D 72B (Nvidia, 2024-10-22): 3.0e24 FLOP, confidence ConfidentDoubao-pro (ByteDance, 2024-10-28): 2.5e25 FLOP, confidence LikelyHunyuan-Large (Tencent, 2024-11-06): 3.5e24 FLOP, confidence ConfidentAmazon Nova Pro (Amazon, 2024-12-03): 6.0e24 FLOP, confidence SpeculativeLlama 3.3 70B (Meta AI, 2024-12-06): 6.9e24 FLOP, confidence ConfidentEXAONE 3.5 32B (LG AI Research, 2024-12-09): 1.3e24 FLOP, confidence ConfidentDeepSeek-V3 (DeepSeek, 2024-12-24): 3.3e24 FLOP, confidence ConfidentEurus-2-7B-PRIME (Tsinghua University,University of Illinois Urbana-Champaign (UIUC),Shanghai AI Lab,Peking University,Shanghai Jiao Tong University,CUHK Shenzhen Research Institute, 2025-01-02): 4.0e20 FLOP, confidence SpeculativeEagle 2 (Nvidia,Nanjing University,Tsinghua University,Hong Kong Polytechnic University,Johns Hopkins University,New York University (NYU), 2025-01-20): 4.7e22 FLOP, confidence ConfidentDeepSeek-R1 (DeepSeek, 2025-01-20): 3.5e24 FLOP, confidence ConfidentGrok 3 (xAI, 2025-02-17): 3.5e26 FLOP, confidence LikelyClaude 3.7 Sonnet (Anthropic, 2025-02-24): 3.4e25 FLOP, confidence LikelyGPT-4.5 (OpenAI, 2025-02-27): 3.8e26 FLOP, confidence LikelyQwQ-32B (Alibaba, 2025-03-06): 3.5e24 FLOP, confidence SpeculativeHunyuan-TurboS (Tencent, 2025-03-11): 5.4e24 FLOP, confidence ConfidentEXAONE Deep 32B (LG AI Research, 2025-03-16): 1.3e24 FLOP, confidence ConfidentDeepSeek-V3 (Mar 2025) (DeepSeek, 2025-03-24): 3.3e24 FLOP, confidence ConfidentLlama 4 Scout (Meta AI, 2025-04-05): 4.1e24 FLOP, confidence LikelyLlama 4 Maverick (Meta AI, 2025-04-05): 2.2e24 FLOP, confidence LikelyLlama 4 Behemoth (preview) (Meta AI, 2025-04-05): 5.2e25 FLOP, confidence LikelyPangu Ultra (Huawei, 2025-04-10): 1.1e25 FLOP, confidence ConfidentQwen3-235B-A22B (Alibaba, 2025-04-29): 4.8e24 FLOP, confidence LikelySeed1.5-VL (ByteDance, 2025-05-11): 1.4e24 FLOP, confidence ConfidentDeepSeek-R1 (May 2025) (DeepSeek, 2025-05-28): 4.0e24 FLOP, confidence ConfidentFGN (Google DeepMind, 2025-06-12): 9.6e21 FLOP, confidence ConfidentGrok 4 (xAI, 2025-07-09): 5.0e26 FLOP, confidence SpeculativeKimi K2 (Moonshot, 2025-07-11): 3.0e24 FLOP, confidence ConfidentEXAONE 4.0 (32B) (LG AI Research, 2025-07-15): 2.7e24 FLOP, confidence ConfidentQwen3-Coder-480B-A35B (Alibaba, 2025-07-22): 1.6e24 FLOP, confidence ConfidentQwen3-235B-A22B-Thinking (Jul 2025) (Alibaba, 2025-07-25): 4.8e24 FLOP, confidence LikelyQwen3-235B-A22B (Jul 2025) (Alibaba, 2025-07-25): 4.8e24 FLOP, confidence LikelyGLM-4.5 (Z.ai (Zhipu AI),Tsinghua University, 2025-07-28): 4.4e24 FLOP, confidence Confidentgpt-oss-120b (OpenAI, 2025-08-05): 4.9e24 FLOP, confidence Confidentgpt-oss-20b (OpenAI, 2025-08-05): 5.5e23 FLOP, confidence ConfidentGPT-5 (OpenAI, 2025-08-07): 6.6e25 FLOP, confidence SpeculativeLongCat-Flash (Meituan Inc, 2025-09-01): 3.7e24 FLOP, confidence LikelyQwen3-Max (Alibaba, 2025-09-05): 1.5e25 FLOP, confidence SpeculativeAgentFounder-30B (Alibaba, 2025-09-16): 6.5e23 FLOP, confidence ConfidentQwen3-Omni-30B-A3B (Alibaba, 2025-09-22): 3.6e22 FLOP, confidence ConfidentGLM-4.6 (Z.ai (Zhipu AI),Tsinghua University, 2025-09-30): 4.4e24 FLOP, confidence LikelyLing-1T (Ant Group, 2025-10-10): 6.0e24 FLOP, confidence ConfidentKimi K2 Thinking (Moonshot, 2025-11-06): 4.2e24 FLOP, confidence LikelyOlmo 3 (Allen Institute for AI, 2025-11-20): 1.1e24 FLOP, confidence ConfidentNemotron 3-Nano-30B-A3B (Nvidia, 2025-12-15): 4.8e23 FLOP, confidence LikelyGLM-4.7 (Z.ai (Zhipu AI), 2025-12-22): 4.4e24 FLOP, confidence LikelySolar Open 100B (Upstage, 2025-12-31): 1.4e24 FLOP, confidence ConfidentK-EXAONE (LG AI Research, 2025-12-31): 1.5e24 FLOP, confidence ConfidentKimi K2.5 (Moonshot, 2026-02-02): 5.8e24 FLOP, confidence LikelyGLM-5 (Z.ai (Zhipu AI), 2026-02-12): 6.8e24 FLOP, confidence LikelyComposer 2 (Cursor, 2026-03-19): 2.3e25 FLOP, confidence ConfidentMolmoAct 2 (Allen Institute for AI,University of Washington,National University of Singapore,University of Pennsylvania,Johns Hopkins University,Amazon,Cortex AI, 2026-04-05): 1.1e22 FLOP, confidence LikelyEXAONE 4.5 (LG AI Research, 2026-04-09): 3.9e24 FLOP, confidence ConfidentMiMo-V2.5-Pro (Xiaomi Corp, 2026-04-23): 6.8e24 FLOP, confidence LikelyDeepSeek-V4-Pro (DeepSeek, 2026-04-24): 9.7e24 FLOP, confidence LikelyDeepSeek-V4-Flash (DeepSeek, 2026-04-24): 2.5e24 FLOP, confidence LikelyComposer 2.5 (Cursor, 2026-05-18): 3.9e25 FLOP, confidence LikelyNemotron 3 Ultra (Nvidia, 2026-06-04): 6.6e24 FLOP, confidence LikelySolar Open2 250B (Upstage, 2026-06-28): 1.1e24 FLOP, confidence LikelyLongCat-2.0 (Meituan Inc, 2026-06-29): 1.0e25 FLOP, confidence LikelyInkling (Thinking Machines, 2026-07-15): 1.1e25 FLOP, confidence LikelyKimi K3 (Moonshot, 2026-07-16): 2.0e25 FLOP, confidence SpeculativeA.X K2 (SK Telecom, 2026-07-29): 1.8e24 FLOP, confidence ConfidentK-EXAONE 2.0 (LG AI Research, 2026-07-31): 3.5e24 FLOP, confidence ConfidentMotif-3 (Motif Technologies, 2026-08-07): 1.1e24 FLOP, confidence ConfidentGLM-5.3-Flash (Z.ai (Zhipu AI), 2026-08-20): 3.2e24 FLOP, confidence LikelyWeatherNext 3 (Google DeepMind,Google Research, 2026-09-03): 2.1e23 FLOP, confidence SpeculativeGPT-6 Astra (OpenAI, 2026-09-03): 9.4e26 FLOP, confidence LikelyDeepSeek V4.1 Flash (DeepSeek, 2026-09-09): 4.3e24 FLOP, confidence LikelyPublication yearTraining compute, FLOP
Reported model Largest run to date EU systemic-risk threshold 468 models published 2012 onward with a compute figure. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , today Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Compute figures are frequently estimated rather than disclosed, and Epoch marks its own confidence on each. Faded points are the ones marked speculative. Models whose compute is unknown are absent entirely, which biases the picture toward labs that publish.

Page: Capability

How far behind open weights are

Largest training run to date, all models against open-weight models. 8 months between the overall frontier reaching 3.8e25 FLOP and an open-weight model doing so.

1e171e191e211e231e251e272016201820202022202420268 months behind
all models open weights Running maximum of training compute by publication date. Accessibility is Epoch's classification; models with no accessibility recorded are counted in the overall line and not in the open-weight one. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , today Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , today Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Both lines are running maxima, so a flat stretch means no larger run has been reported, not that anything got smaller. Compute figures are frequently estimates and arrive late, so the right-hand end of the overall line is a lower bound.

Page: Capability

Compute thresholds in law

4 of 6 thresholds were written after a model had already crossed them. Each mark is the day an instrument took its final form.

1e241e251e261e2720232024202520262027EO 14110, 2023-10EU AI Act, 2024-06SB 1047, 2024-09SB 53, 2025-09RAISE Act, 2025-12Korean decree, 2026-01
Reported model Largest run to date In force Enacted, not yet applicable Revoked, or a vetoed bill Thresholds are our own index of primary instruments. Model compute figures are Epoch's. Compute Threshold Index This site Licence MIT Updated quarterly Retrieved , 5 days ago Data JSON CSV Training-compute thresholds written into law, executive action or published policy, with the text that sets each one. Whether a given model crosses a threshold here is arithmetic on Epoch's compute estimates, most of which are estimates rather than disclosures, and is not a legal finding about any model or developer. Cite AI Safety Tracker, "Compute Threshold Index". https://aisafetytracker.org/capability/#thresholds. Retrieved 23 October 2026. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , 5 days ago Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 23 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Whether a model sits above a line is arithmetic on Epoch's compute figures, most of which are estimates rather than disclosures. Nothing here is a legal finding about any model or developer.

Page: Capability

Where AI datacentres are

Every site in Epoch AI's AI Data Centers hub, sized by IT power. The ring is the power planned at the site's last projected stage, the disc the power operating now. Dashed rings are sites the hub does not hold, sized by the capacity their developers state.

Microsoft Fairwater Wisconsin Mount Pleasant, Wisconsin, United States
Status
Operating, expanding, online since Apr 2026
IT power
369 MW now, 2.3 GW by May 2028
Facility power
442 MW now, 2.7 GW by May 2028
Compute
446,000 H100e now, 4.5 million H100e by May 2028
Chips
B200
Owner of chips
Microsoft
Used by
OpenAI (likely) and Microsoft (likely)
Project
Microsoft AI WAN
Not recorded
Training or inference, power source, cooling type
Row in the list
Anthropic-Amazon New Carlisle New Carlisle, Indiana, United States
Status
Operating, expanding, online since Jun 2025
IT power
1 GW now, 1.9 GW by Mar 2028
Facility power
1.2 GW now, 2.3 GW by Mar 2028
Compute
818,000 H100e now, 1.7 million H100e by Mar 2028
Chips
Trainium2
Owner of chips
Amazon
Used by
Anthropic
Project
Project Rainier
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate New Mexico Santa Teresa, New Mexico, United States
Status
Under construction, due online Dec 2028
IT power
1.8 GW by Dec 2028
Facility power
2.5 GW by Dec 2028
Compute
5.1 million H100e by Dec 2028
Chips
not recorded
Owner of chips
Oracle
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Hyperion Holly Ridge, Louisiana, United States
Status
Under construction, due online Jan 2028
IT power
1.6 GW by Jan 2028
Facility power
2.2 GW by Jan 2028
Compute
4.1 million H100e by Jan 2028
Chips
Rubin
Owner of chips
Meta
Used by
Meta
Project
Hyperion
Not recorded
Training or inference, power source, cooling type
Row in the list
Colossus 2 Memphis, Tennessee, United States
Status
Operating, expanding, online since Oct 2025
IT power
946 MW now, 1.5 GW by Feb 2027
Facility power
1.3 GW now, 2.1 GW by Feb 2027
Compute
1.1 million H100e now, 1.8 million H100e by Feb 2027
Chips
B200, B300
Owner of chips
SpaceXAI
Used by
Anthropic, Cursor and SpaceXAI
Not recorded
Training or inference, power source, cooling type
Row in the list
Western Downs Digital Park Near Dalby, Queensland, Australia
Status
Proposed, due 2027
Capacity
Up to 1.44 GW of IT capacity in four stages, each designed for about 540 MVA of total facility demand.
Developer
Zerra DC
Used by
Anthropic (lease signed, subject to approvals)
Use
Inference, as reported by the press
Power supply
Grid, through a dedicated connection at Braemar substation, beside the gas-fired Braemar 1 and 2 power stations. Generation contracts for each stage not yet set.
Cooling
Air-cooled, closed loop, with no evaporative cooling.
Location
Approximate: placed at the town or reported area
Row in the added sites
OpenAI Stargate Shackelford Abilene, Texas, United States
Status
Under construction, due online Aug 2027
IT power
1.4 GW by Nov 2028
Facility power
2 GW by Nov 2028
Compute
4.6 million H100e by Nov 2028
Chips
Rubin
Owner of chips
Oracle
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Firmus Stirling North Stirling North, South Australia, Australia
Status
Proposed
Capacity
About 1.3 GW of critical IT load at full build, on about 1.5 GW of planned grid connection.
Developer
Firmus
Used by
not named
Use
not stated
Power supply
A 12-year agreement with Gunvor for 600 MW across the first phase of both South Australian campuses, tied to 1.2 GW of new renewable generation and 1.5 GWh of batteries by 2032.
Cooling
not stated
Location
Approximate: placed at the town or reported area
Row in the added sites
QTS Cedar Rapids Cedar Rapids, Iowa, United States
Status
Under construction, due online Nov 2026
IT power
1.1 GW by Nov 2027
Facility power
1.6 GW by Nov 2027
Compute
3.7 million H100e by Nov 2027
Chips
Rubin
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Prometheus New Albany, Ohio, United States
Status
Operating, expanding, online since Oct 2025
IT power
471 MW now, 1 GW by Jul 2028
Facility power
612 MW now, 1.3 GW by Jul 2028
Compute
536,000 H100e now, 1.2 million H100e by Jul 2028
Chips
B300
Owner of chips
Meta
Used by
Meta
Project
Prometheus
Not recorded
Training or inference, power source, cooling type
Row in the list
Goodnight Claude, Texas, United States
Status
Under construction, due online Mar 2027
IT power
1 GW by Oct 2027
Facility power
1.3 GW by Oct 2027
Compute
2.3 million H100e by Oct 2027
Chips
B300, Rubin
Owner of chips
Google (speculative)
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate UAE Abu Dhabi, Abu Dhabi, United Arab Emirates
Status
Under construction, due online Dec 2026
IT power
1 GW by Jan 2028
Facility power
1.4 GW by Jan 2028
Compute
2 million H100e by Jan 2028
Chips
B300, Rubin
Owner of chips
G42 (likely)
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Firmus Tailem Bend Tailem Bend, South Australia, Australia
Status
Proposed
Capacity
About 1.0 GW of critical IT load at full build, on about 1.2 GW of planned grid connection.
Developer
Firmus
Used by
not named
Use
not stated
Power supply
A 12-year agreement with Gunvor for 600 MW across the first phase of both South Australian campuses, tied to 1.2 GW of new renewable generation and 1.5 GWh of batteries by 2032.
Cooling
not stated
Location
Approximate: placed at the town or reported area
Row in the added sites
OpenAI Stargate Michigan Benton, Michigan, United States
Status
Under construction, due online Dec 2028
IT power
988 MW by Dec 2028
Facility power
1.4 GW by Dec 2028
Compute
2.9 million H100e by Dec 2028
Chips
not recorded
Owner of chips
Oracle
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate Wisconsin Port Washington, Wisconsin, United States
Status
Under construction, due online Dec 2028
IT power
902 MW by Dec 2028
Facility power
1.3 GW by Dec 2028
Compute
2.6 million H100e by Dec 2028
Chips
not recorded
Owner of chips
Oracle
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Fort Wayne Fort Wayne, Indiana, United States
Status
Under construction, due online Dec 2026
IT power
863 MW by Jun 2028
Facility power
1 GW by Jun 2028
Compute
2.9 million H100e by Jun 2028
Chips
not recorded
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate Milam Burlington, Texas, United States
Status
Under construction, due online Dec 2028
IT power
857 MW by Dec 2028
Facility power
1.2 GW by Dec 2028
Compute
2.5 million H100e by Dec 2028
Chips
not recorded
Owner of chips
Softbank
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate Abilene Abilene, Texas, United States
Status
Operating, expanding, online since Sept 2025
IT power
421 MW now, 843 MW by Nov 2026
Facility power
590 MW now, 1.2 GW by Nov 2026
Compute
509,000 H100e now, 1 million H100e by Nov 2026
Chips
B200, B300
Owner of chips
Oracle
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Amazon Ridgeland Ridgeland, Mississippi, United States
Status
Operating, expanding, online since May 2026
IT power
228 MW now, 840 MW by Sept 2028
Facility power
273 MW now, 1 GW by Sept 2028
Compute
171,000 H100e now, 788,000 H100e by Sept 2028
Chips
Trainium2, Trainium3
Owner of chips
Amazon
Used by
Anthropic (speculative)
Project
Project Rainier (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
IREN Bundey Bundey, South Australia, Australia
Status
Proposed, due 2028
Capacity
800 MW of transmission connection. IT capacity not stated.
Developer
IREN
Used by
not named
Use
not stated
Power supply
Four 330 kV feeders at the Bundey substation, supporting up to 800 MW.
Cooling
not stated
Location
Approximate: placed at the town or reported area
Row in the added sites
VNET Bayin Ulanqab Ulanqab, Inner Mongolia, China
Status
Operating, expanding, online since Jul 2025
IT power
221 MW now, 700 MW by Sept 2027
Facility power
252 MW now, 798 MW by Sept 2027
Compute
123,000 H100e now, 388,000 H100e by Sept 2027
Chips
Ascend 910C
Owner of chips
VNET
Used by
ByteDance (speculative)
Project
10 GW Hyperscale 2.0
Not recorded
Training or inference, power source, cooling type
Row in the list
Amazon Madison Mega Site Canton, Mississippi, United States
Status
Operating, expanding, online since Jun 2025
IT power
284 MW now, 683 MW by Mar 2028
Facility power
341 MW now, 819 MW by Mar 2028
Compute
214,000 H100e now, 514,000 H100e by Mar 2028
Chips
Trainium2
Owner of chips
Amazon
Used by
Anthropic (speculative)
Project
Project Rainier (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Crusoe Abilene Expansion Abilene, Texas, United States
Status
Under construction, due online Sept 2027
IT power
672 MW by Nov 2027
Facility power
941 MW by Nov 2027
Compute
1.7 million H100e by Nov 2027
Chips
Rubin
Owner of chips
Microsoft
Used by
Microsoft (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft Fairwater Atlanta Fayetteville, Georgia, United States
Status
Operating, online since Oct 2025
IT power
636 MW
Facility power
859 MW
Compute
769,000 H100e
Chips
B200
Owner of chips
Microsoft
Used by
OpenAI (likely) and Microsoft (likely)
Project
Microsoft AI WAN
Not recorded
Training or inference, power source, cooling type
Row in the list
NEXTDC S7 Sydney Eastern Creek, New South Wales, Australia
Status
Proposed, due 2027
Capacity
550 MW or more.
Developer
NEXTDC
Used by
OpenAI (non-binding memorandum of understanding, December 2025)
Use
not stated
Power supply
not stated
Cooling
Closed-loop liquid cooling, using no potable water.
Location
Approximate: placed at the town or reported area
Row in the added sites
Coreweave Helios Afton, Texas, United States
Status
Operating, expanding, online since Aug 2026
IT power
132 MW now, 528 MW by Jan 2029
Facility power
200 MW now, 800 MW by Jan 2029
Compute
160,000 H100e now, 638,000 H100e by Jan 2029
Chips
B200
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
DayOne Nusajaya Johor Bahru, Johor, Malaysia
Status
Operating, online since Dec 2024
IT power
473 MW
Facility power
662 MW
Compute
584,000 H100e
Chips
H100, B300
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Envision Galaxy Ulanqab Ulanqab, Inner Mongolia, China
Status
Under construction, due online Nov 2026
IT power
470 MW by Dec 2027
Facility power
612 MW by Dec 2027
Compute
170,000 H100e by Dec 2027
Chips
Ascend 950PR, Ascend 950DT
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Huawei Wuhu Wuhu, Anhui, China
Status
Operating, expanding, online since Jan 2025
IT power
157 MW now, 457 MW by Dec 2027
Facility power
181 MW now, 526 MW by Dec 2027
Compute
76,000 H100e now, 222,000 H100e by Dec 2027
Chips
Ascend 910C
Owner of chips
Huawei
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Bowling Green Bowling Green, Ohio, United States
Status
Under construction, due online Feb 2027
IT power
422 MW by Jan 2028
Facility power
570 MW by Jan 2028
Compute
855,000 H100e by Jan 2028
Chips
B300, Rubin
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
DayOne Kempas Kempas, Johor, Malaysia
Status
Operating, online since Jan 2026
IT power
422 MW
Facility power
590 MW
Compute
481,000 H100e
Chips
B300
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Ellendale ND Ellendale, North Dakota, United States
Status
Operating, expanding, online since Oct 2025
IT power
68 MW now, 400 MW by Jun 2027
Facility power
88 MW now, 520 MW by Jun 2027
Compute
93,000 H100e now, 505,000 H100e by Jun 2027
Chips
B200
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Omaha Omaha, Nebraska, United States
Status
Operating, expanding, online since Apr 2024
IT power
237 MW now, 395 MW by Jul 2028
Facility power
284 MW now, 474 MW by Jul 2028
Compute
199,000 H100e now, 904,000 H100e by Jul 2028
Chips
TPU v5e, TPU v5p, TPU v6e, TPU v7
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Columbus Columbus, Ohio, United States
Status
Operating, expanding, online since Apr 2024
IT power
303 MW now, 386 MW by Jul 2027
Facility power
364 MW now, 464 MW by Jul 2027
Compute
332,000 H100e now, 576,000 H100e by Jul 2027
Chips
TPU v5e, TPU v5p, TPU v6e, TPU v7
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Anthropic Lake Mariner Barker, New York, United States
Status
Operating, expanding, online since May 2026
IT power
42 MW now, 378 MW by Mar 2027
Facility power
49 MW now, 441 MW by Mar 2027
Compute
59,000 H100e now, 527,000 H100e by Mar 2027
Chips
TPU v7
Owner of chips
AI XPV Platform
Used by
Anthropic (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Pryor (North) Pryor, Oklahoma, United States
Status
Operating, online since Jul 2024
IT power
368 MW
Facility power
442 MW
Compute
637,000 H100e
Chips
TPU v5p, TPU v5e
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Montgomery Montgomery, Alabama, United States
Status
Operating, expanding, online since Jun 2026
IT power
153 MW now, 358 MW by Feb 2027
Facility power
199 MW now, 465 MW by Feb 2027
Compute
175,000 H100e now, 407,000 H100e by Feb 2027
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
STACK Infrastructure NVA02 Manassas, Virginia, United States
Status
Operating, expanding, online since Oct 2024
IT power
85 MW now, 348 MW by Jan 2028
Facility power
118 MW now, 487 MW by Jan 2028
Compute
61,000 H100e now, 251,000 H100e by Jan 2028
Chips
H100
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Huawei Horinger Hohhot, Inner Mongolia, China
Status
Operating, expanding, online since Jun 2025
IT power
184 MW now, 346 MW by Feb 2028
Facility power
212 MW now, 415 MW by Feb 2028
Compute
89,000 H100e now, 168,000 H100e by Feb 2028
Chips
Ascend 910C
Owner of chips
Huawei
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Colossus 1 Memphis, Tennessee, United States
Status
Operating, online since Aug 2024
IT power
340 MW
Facility power
425 MW
Compute
276,000 H100e
Chips
H100, H200, B200
Owner of chips
SpaceXAI
Used by
Anthropic
Not recorded
Training or inference, power source, cooling type
Row in the list
AWS New Albany New Albany, Ohio, United States
Status
Operating, expanding, online since Dec 2024
IT power
213 MW now, 338 MW by Jul 2027
Facility power
255 MW now, 405 MW by Jul 2027
Compute
201,000 H100e now, 352,000 H100e by Jul 2027
Chips
Trainium2, H100, H200, B200
Owner of chips
Amazon
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Google New Albany New Albany, Ohio, United States
Status
Operating, online since Apr 2024
IT power
333 MW
Facility power
400 MW
Compute
324,000 H100e
Chips
TPU v5e, TPU v5p, TPU v6e
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
QTS Eagle Mountain Eagle Mountain, Utah, United States
Status
Under construction, due online Dec 2026
IT power
304 MW by Jul 2027
Facility power
411 MW by Jul 2027
Compute
347,000 H100e by Jul 2027
Chips
B300
Owner of chips
Meta (speculative)
Used by
Meta (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Storey County Clark, Nevada, United States
Status
Operating, expanding, online since Aug 2023
IT power
161 MW now, 300 MW by Jun 2027
Facility power
214 MW now, 389 MW by Jun 2027
Compute
134,000 H100e now, 541,000 H100e by Jun 2027
Chips
TPU v5e, TPU v4, TPU v6e, TPU v5p
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Firmus Bell Bay Long Reach, Tasmania, Australia
Status
Approved
Capacity
Maximum demand of about 288 MW. IT capacity not stated.
Developer
Firmus
Used by
not named
Use
Training and inference
Power supply
Tasmanian grid, through three 220 kV lines crossing the site. Supply arrangements under negotiation.
Cooling
Direct-to-chip liquid cooling. Dry cooling, with water on about ten hot days a year.
Location
Placed on the stated street
Row in the added sites
Google Lincoln Lincoln, Nebraska, United States
Status
Operating, expanding, online since May 2026
IT power
141 MW now, 283 MW by Oct 2027
Facility power
170 MW now, 339 MW by Oct 2027
Compute
198,000 H100e now, 672,000 H100e by Oct 2027
Chips
TPU v6e, TPU v7
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Denton TX Denton, Texas, United States
Status
Operating, expanding, online since May 2025
IT power
262 MW now, 282 MW by May 2027
Facility power
367 MW now, 395 MW by May 2027
Compute
253,000 H100e now, 272,000 H100e by May 2027
Chips
B200
Owner of chips
CoreWeave
Used by
OpenAI (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Cedar Rapids Cedar Rapids, Iowa, United States
Status
Under construction, due online Dec 2026
IT power
261 MW by May 2027
Facility power
314 MW by May 2027
Compute
670,000 H100e by May 2027
Chips
not recorded
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Bridge Data Centres MY06 Kulai, Johor, Malaysia
Status
Operating, online since Dec 2022
IT power
243 MW
Facility power
315 MW
Compute
221,000 H100e
Chips
A100, H100, B200
Owner of chips
ByteDance (likely)
Used by
ByteDance (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
QTS Richmond 3 Sandston, Virginia, United States
Status
Operating, expanding, online since Feb 2026
IT power
144 MW now, 240 MW by Feb 2027
Facility power
202 MW now, 336 MW by Feb 2027
Compute
175,000 H100e now, 291,000 H100e by Feb 2027
Chips
not recorded
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Bristow Bristow, Virginia, United States
Status
Operating, online since Apr 2024
IT power
238 MW
Facility power
286 MW
Compute
210,000 H100e
Chips
TPU v5e, TPU v5p, TPU v6e, TPU v7
Owner of chips
Google
Used by
Google DeepMind
Not recorded
Training or inference, power source, cooling type
Row in the list
QTS Richmond 1 Sandston, Virginia, United States
Status
Operating, online since Jan 2024
IT power
238 MW
Facility power
333 MW
Compute
243,000 H100e
Chips
not recorded
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Council Bluffs (East) Council Bluffs, Iowa, United States
Status
Operating, online since Nov 2024
IT power
237 MW
Facility power
284 MW
Compute
256,000 H100e
Chips
TPU v5e, TPU v6e, TPU v5p, TPU v7
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Papillion Papillion, Nebraska, United States
Status
Operating, online since Jan 2023
IT power
237 MW
Facility power
284 MW
Compute
101,000 H100e
Chips
TPU v4, TPU v5e, TPU v5p
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Start Campus Sines Data Campus Sines, Setúbal, Portugal
Status
Operating, expanding, online since Apr 2026
IT power
33 MW now, 233 MW by Sept 2027
Facility power
40 MW now, 280 MW by Sept 2027
Compute
32,000 H100e now, 541,000 H100e by Sept 2027
Chips
B300
Owner of chips
Nscale
Used by
Microsoft
Not recorded
Training or inference, power source, cooling type
Row in the list
Stream Phoenix Goodyear, Arizona, United States
Status
Operating, expanding, online since May 2026
IT power
64 MW now, 220 MW by Jan 2030
Facility power
77 MW now, 267 MW by Jan 2030
Compute
46,000 H100e now, 160,000 H100e by Jan 2030
Chips
H100
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Los Lunas Los Lunas, New Mexico, United States
Status
Operating, expanding, online since Mar 2026
IT power
118 MW now, 218 MW by Jan 2028
Facility power
147 MW now, 273 MW by Jan 2028
Compute
134,000 H100e now, 869,000 H100e by Jan 2028
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
OpenAI Stargate Lordstown Lordstown, Ohio, United States
Status
Under construction, due online Mar 2027
IT power
214 MW by Mar 2027
Facility power
300 MW by Mar 2027
Compute
546,000 H100e by Mar 2027
Chips
Rubin
Owner of chips
Softbank
Used by
OpenAI
Project
Stargate
Not recorded
Training or inference, power source, cooling type
Row in the list
Anthropic Barber Lake Colorado City, Texas, United States
Status
Under construction, due online Dec 2026
IT power
207 MW by Apr 2027
Facility power
300 MW by Apr 2027
Compute
289,000 H100e by Apr 2027
Chips
TPU v7
Owner of chips
Cipher Mining
Used by
Anthropic
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Cheyenne Cheyenne, Wyoming, United States
Status
Operating, expanding, online since Jul 2026
IT power
152 MW now, 207 MW by Feb 2027
Facility power
182 MW now, 249 MW by Feb 2027
Compute
173,000 H100e now, 236,000 H100e by Feb 2027
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft Goodyear Goodyear, Arizona, United States
Status
Operating, online since Apr 2023
IT power
202 MW
Facility power
263 MW
Compute
205,000 H100e
Chips
H100, B200
Owner of chips
Microsoft
Used by
OpenAI (likely) and Microsoft
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft Project Osmium Cumming, Iowa, United States
Status
Operating, online since Jan 2021
IT power
190 MW
Facility power
228 MW
Compute
156,000 H100e
Chips
A100, H100, B200
Owner of chips
Microsoft
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Mesa Mesa, Arizona, United States
Status
Operating, online since Jul 2025
IT power
183 MW
Facility power
237 MW
Compute
290,000 H100e
Chips
TPU v6e, TPU v5p
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta-QTS Hillsboro 2 Hillsboro, Oregon, United States
Status
Operating, online since Aug 2023
IT power
180 MW
Facility power
243 MW
Compute
124,000 H100e
Chips
H100
Owner of chips
Meta (likely)
Used by
Meta (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
QTS Richmond 2 Sandston, Virginia, United States
Status
Operating, online since Feb 2025
IT power
180 MW
Facility power
252 MW
Compute
183,000 H100e
Chips
not recorded
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Jeffersonville Jeffersonville, Indiana, United States
Status
Operating, online since Jun 2026
IT power
178 MW
Facility power
241 MW
Compute
203,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Rosemount Rosemount, Minnesota, United States
Status
Operating, online since Jun 2026
IT power
178 MW
Facility power
241 MW
Compute
216,000 H100e
Chips
B200
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Temple Temple, Texas, United States
Status
Operating, online since Dec 2025
IT power
178 MW
Facility power
231 MW
Compute
202,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Alibaba Zhangbei Zhangbei, Hebei, China
Status
Operating, online since Sept 2025
IT power
169 MW
Facility power
203 MW
Compute
32,000 H100e
Chips
H20
Owner of chips
Alibaba
Used by
Alibaba (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
AWS Berwick Berwick, Pennsylvania, United States
Status
Operating, expanding, online since Sept 2025
IT power
108 MW now, 169 MW by Aug 2027
Facility power
139 MW now, 212 MW by Aug 2027
Compute
81,000 H100e now, 145,000 H100e by Aug 2027
Chips
Trainium2, Trainium3
Owner of chips
Amazon
Used by
Anthropic (speculative)
Project
Project Rainier (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Red Oak Red Oak, Texas, United States
Status
Operating, expanding, online since Aug 2025
IT power
77 MW now, 154 MW by Dec 2026
Facility power
93 MW now, 185 MW by Dec 2026
Compute
108,000 H100e now, 279,000 H100e by Dec 2026
Chips
TPU v6e
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Google The Dalles The Dalles, Oregon, United States
Status
Operating, online since Mar 2025
IT power
154 MW
Facility power
185 MW
Compute
175,000 H100e
Chips
TPU v6e, TPU v5p, TPU v5e, TPU v7
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Muskogee OK Muskogee, Oklahoma, United States
Status
Under construction, due online Dec 2026
IT power
153 MW by Dec 2027
Facility power
181 MW by Dec 2027
Compute
198,000 H100e by Dec 2027
Chips
B300
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Kuna Kuna, Idaho, United States
Status
Operating, online since Jun 2026
IT power
152 MW
Facility power
198 MW
Compute
173,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Huntsville Huntsville, Alabama, United States
Status
Operating, online since Mar 2026
IT power
146 MW
Facility power
198 MW
Compute
167,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Nebius Mantsala Mantsala, Uusimaa, Finland
Status
Operating, expanding, online since Oct 2024
IT power
75 MW now, 145 MW by Dec 2027
Facility power
90 MW now, 196 MW by Dec 2027
Compute
49,000 H100e now, 226,000 H100e by Dec 2027
Chips
H100, B300, H200
Owner of chips
Nebius
Used by
Microsoft (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Lancaster Lancaster, Ohio, United States
Status
Operating, online since Jan 2024
IT power
137 MW
Facility power
164 MW
Compute
130,000 H100e
Chips
TPU v5e, TPU v6e
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Eagle Mountain Eagle Mountain, Utah, United States
Status
Operating, online since Dec 2025
IT power
133 MW
Facility power
179 MW
Compute
151,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Aiken Aiken, South Carolina, United States
Status
Operating, expanding, online since Aug 2026
IT power
69 MW now, 129 MW by Nov 2026
Facility power
90 MW now, 168 MW by Nov 2026
Compute
78,000 H100e now, 147,000 H100e by Nov 2026
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Vantage TX1 San Antonio, Texas, United States
Status
Operating, expanding, online since Feb 2026
IT power
32 MW now, 128 MW by Aug 2027
Facility power
44.8 MW now, 179 MW by Aug 2027
Compute
39,000 H100e now, 155,000 H100e by Aug 2027
Chips
B200
Owner of chips
not recorded
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Chester VA Chester, Virginia, United States
Status
Operating, expanding, online since Jan 2024
IT power
82 MW now, 113 MW by Jun 2027
Facility power
114 MW now, 197 MW by Jun 2027
Compute
88,000 H100e now, 126,000 H100e by Jun 2027
Chips
H100, B200
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Kansas City East Kansas City, Missouri, United States
Status
Operating, online since Aug 2026
IT power
105 MW
Facility power
126 MW
Compute
203,000 H100e
Chips
not recorded
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Midlothian Midlothian, Texas, United States
Status
Operating, online since Apr 2026
IT power
103 MW
Facility power
123 MW
Compute
144,000 H100e
Chips
TPU v7, TPU v6e
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Lancaster Greenfield site Lancaster, Pennsylvania, United States
Status
Under construction, due online Jun 2027
IT power
92 MW by Jun 2027
Facility power
124 MW by Jun 2027
Compute
233,000 H100e by Jun 2027
Chips
Rubin
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft Narvik Norway Bjerkvik, Narvik, Norway
Status
Under construction, due online Dec 2026
IT power
92 MW by Dec 2026
Facility power
124 MW by Dec 2026
Compute
265,000 H100e by Dec 2026
Chips
Rubin
Owner of chips
Nscale (likely)
Used by
Microsoft (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Waltham Cross Cheshunt, Hertfordshire, United Kingdom
Status
Operating, online since Sept 2025
IT power
88 MW
Facility power
124 MW
Compute
124,000 H100e
Chips
TPU v6e
Owner of chips
Google
Used by
Google DeepMind (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Gallatin United States
Status
Operating, online since Aug 2026
IT power
87 MW
Facility power
114 MW
Compute
100,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Meta Sarpy Springfield, Nebraska, United States
Status
Operating, online since Aug 2026
IT power
80 MW
Facility power
105 MW
Compute
92,000 H100e
Chips
B300
Owner of chips
Meta
Used by
Meta
Not recorded
Training or inference, power source, cooling type
Row in the list
Google Arcola Arcola, Virginia, United States
Status
Operating, online since Jun 2026
IT power
77 MW
Facility power
93 MW
Compute
108,000 H100e
Chips
TPU v6e, TPU v7
Owner of chips
Google
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft SAT40 San Antonio, Texas, United States
Status
Operating, online since May 2024
IT power
75 MW
Facility power
106 MW
Compute
65,000 H100e
Chips
H100, B300
Owner of chips
Microsoft
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
Oracle Batam Batam, Riau Islands, Indonesia
Status
Operating, online since May 2025
IT power
72 MW
Facility power
94 MW
Compute
84,000 H100e
Chips
B200, B300
Owner of chips
Oracle (likely)
Used by
Tencent (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Marble NC Marble, North Carolina, United States
Status
Operating, online since Mar 2026
IT power
65 MW
Facility power
91 MW
Compute
79,000 H100e
Chips
B200
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Core42 Lake Mariner Barker, New York, United States
Status
Operating, online since Oct 2025
IT power
58 MW
Facility power
58 MW
Compute
72,000 H100e
Chips
B200
Owner of chips
Core42
Used by
G42 (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft-Nebius New Jersey Vineland, New Jersey, United States
Status
Operating, online since Apr 2026
IT power
50 MW
Facility power
70 MW
Compute
57,000 H100e
Chips
B300
Owner of chips
Nebius
Used by
Microsoft (likely)
Not recorded
Training or inference, power source, cooling type
Row in the list
EcoDataCenter 2 Borlänge, Dalarna County, Sweden
Status
Under construction, due online Jun 2027
IT power
48 MW by Jun 2028
Facility power
67 MW by Jun 2028
Compute
139,000 H100e by Jun 2028
Chips
Rubin
Owner of chips
Mistral AI
Used by
Mistral AI
Not recorded
Training or inference, power source, cooling type
Row in the list
Microsoft SAT14 San Antonio, Texas, United States
Status
Operating, online since Jul 2024
IT power
47 MW
Facility power
66 MW
Compute
45,000 H100e
Chips
H100, B300
Owner of chips
Microsoft
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Norway Øvrebø, Agder, Norway
Status
Operating, online since Jul 2025
IT power
42 MW
Facility power
55 MW
Compute
51,000 H100e
Chips
B200
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
Southgate Melbourne Melbourne, Victoria, Australia
Status
Operating, online since Aug 2026
IT power
41 MW
Facility power
57 MW
Compute
46,000 H100e
Chips
B300
Owner of chips
Firmus
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
CoreWeave Dalton 1 & 2 Dalton, Georgia, United States
Status
Operating, online since Feb 2026
IT power
28 MW
Facility power
40 MW
Compute
32,000 H100e
Chips
B300
Owner of chips
CoreWeave
Used by
OpenAI (speculative)
Not recorded
Training or inference, power source, cooling type
Row in the list
xAI QTS Atlanta Atlanta, Georgia, United States
Status
Operating, online since Feb 2025
IT power
17.3 MW
Facility power
24 MW
Compute
11,000 H100e
Chips
H100, A100
Owner of chips
SpaceXAI
Used by
SpaceXAI
Not recorded
Training or inference, power source, cooling type
Row in the list
Nscale Keflavik Reykjanesbær, Suðurnes, Iceland
Status
Operating, expanding, online since Apr 2026
IT power
5.1 MW now, 10.2 MW by Dec 2026
Facility power
6.6 MW now, 13.3 MW by Dec 2026
Compute
6,000 H100e now, 12,000 H100e by Dec 2026
Chips
B300
Owner of chips
Nscale
Used by
not recorded
Not recorded
Training or inference, power source, cooling type
Row in the list
NEXTDC M4 Melbourne Port Melbourne, Victoria, Australia
Status
Approved
Capacity
Targeting 150 MW of IT capacity, within a 162 MW campus.
Developer
NEXTDC
Used by
not named
Use
not stated
Power supply
not stated
Cooling
Direct-to-chip, closed-loop liquid cooling, using recycled water.
Location
Placed on the stated street
Row in the added sites
Firmus Launceston St Leonards, Launceston, Tasmania, Australia
Status
Under construction, due 2027
Capacity
84 MW of critical IT load.
Developer
Firmus
Used by
not named
Use
Training and inference
Power supply
Tasmanian grid, which Firmus describes as firmed hydro, wind and solar.
Cooling
Primarily direct-to-chip liquid cooling.
Location
Placed on the stated street
Row in the added sites
Macquarie IC3 Super West Macquarie Park, New South Wales, Australia
Status
Under construction, due Sept 2026
Capacity
47 MW.
Developer
Macquarie Data Centres
Used by
not named
Use
not stated
Power supply
not stated
Cooling
Air, liquid and hybrid cooled halls.
Location
Placed at the site
Row in the added sites
Firmus Wesley Vale Wesley Vale, Tasmania, Australia
Status
Proposed
Capacity
Two stages: 23 MW of critical IT load, then about 46 MW, drawing up to about 52 MW.
Developer
Firmus
Used by
not named
Use
Training and inference
Power supply
Grid, through the adjoining Wesley Vale substation, starting with a 26 MW connection.
Cooling
Liquid cooling, with adiabatic coolers and chillers that use water in hot weather.
Location
Placed on the stated street
Row in the added sites
NEXTDC S6 Sydney Artarmon, New South Wales, Australia
Status
Operating
Capacity
13.5 MW.
Developer
NEXTDC
Used by
not named
Use
not stated
Power supply
not stated
Cooling
High-density liquid cooling.
Location
Placed at the site
Row in the added sites
NEXTDC M3 Melbourne West Footscray, Victoria, Australia
Status
Operating
Capacity
225 MW for the whole facility. The AI tenant's share is not stated.
Developer
NEXTDC
Used by
Sharon AI (cluster of 1,000 Nvidia B200 GPUs announced January 2026)
Use
not stated
Power supply
not stated
Cooling
not stated
Location
Placed at the site
Row in the added sites
100 MW 500 MW 2 GW Disc: operating now Dashed: stated by the developer Solid rings: locations, owners, users, power and compute are Epoch AI's. Dashed rings: recorded by this site from developers' statements, placed at each stated address or area. Land and borders are Natural Earth's. Marker area is proportional to power, with a floor so the smallest sites stay visible. AI Data Centers Epoch AI Licence CC-BY-4.0 Updated several times a week Retrieved , 10 days ago The largest AI sites Epoch has found, mostly in the United States. Epoch estimated in September 2026 that they hold 44% of the world's deployed AI compute, with a 90% interval of 23% to 81%. Power, compute and cost are Epoch's estimates from satellite imagery, permits and company statements; four in five IT power estimates fall within a factor of 1.4 of the true value. The owner is the owner of the chips, not necessarily of the building. Capacity after the date of retrieval is Epoch's projection. Coordinates are read from the hub's map page, which publishes them; the downloads do not. Cite Epoch AI, "AI Data Centers". https://epoch.ai/data/ai-data-centers. Retrieved 18 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/. AI Datacentre Index This site Licence MIT Updated quarterly Retrieved , 10 days ago Data JSON AI datacentre sites that Epoch AI's hub does not hold, recorded from the statements of developers, named tenants and planning authorities. Australia only so far. A site is included only where a primary source says it is built for AI compute or names the AI deployment inside it. Capacity is as the developer states it, IT or facility power as labelled, and is not an estimate; most of it is proposed and not yet approved. Coordinates are this site's placement of each stated address or area. Cite AI Safety Tracker, "AI Datacentre Index". https://aisafetytracker.org/datacentres/#added. Retrieved 18 October 2026. Natural Earth country boundaries, 1:110m Natural Earth Licence public-domain Updated irregular Retrieved , 10 days ago Public domain, with no permission needed and no attribution required; we credit it anyway because a boundary is a datum like any other. Consumed through the world-atlas package at build time, at 1:110m, so small island states are absent or a single pixel. Boundaries follow Natural Earth's own editorial choices on disputed territory and are not a position of this site. Antarctica is dropped from our render. Cite Natural Earth, "Natural Earth country boundaries, 1:110m". https://www.naturalearthdata.com/about/terms-of-use/. Retrieved 18 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

The largest AI sites Epoch has found, mostly in the United States. Epoch estimated in September 2026 that they hold 44% of the world's deployed AI compute, with a 90% interval of 23% to 81%. Power, compute and cost are Epoch's estimates from satellite imagery, permits and company statements; four in five IT power estimates fall within a factor of 1.4 of the true value. The owner is the owner of the chips, not necessarily of the building. Capacity after the date of retrieval is Epoch's projection. Coordinates are read from the hub's map page, which publishes them; the downloads do not. IT power is the power available to the computing equipment; facility power adds cooling and other overheads.

Page: Datacentres

Datacentre electricity to 2035

Electricity used by all datacentres worldwide: the International Energy Agency's estimate for 2024 and 2025, and its Base Case for 2030 and 2035. The 2035 range spans its four cases. The AI portion is marked where the agency states one.

04008001,2001,600202420252026202720282029203020312032203320342035Electricity used by datacentres, TWh a year1,700, top of range700, foot of range2024: 415 TWh, estimated by the IEA2025: 485 TWh, estimated by the IEA2030: about 945 TWh, IEA Base Case2035: about 1,200 TWh, IEA Base Case4154859451,200, Base Case2024: about 62 TWh used by accelerated servers, 15% of the total2030: about 465 TWh at AI-focused datacentres, IEA Base Case62, accelerated servers465, AI-focused datacentres
All datacentres, estimated All datacentres, IEA Base Case Range across the four cases AI portion, defined differently each year Every figure is the IEA's, read from Energy and AI (2025) and Key Questions on Energy and AI (2026). The dashed line joins the years the IEA states. Nothing is this site's forecast. Environmental Disclosure Index This site Licence MIT Updated quarterly Retrieved , 4 days ago Data 7 datasets Our own reading of what frontier developers and the operators of their data centres have published about training energy, emissions, power sources and energy per prompt, with permits and press reporting marked separately from company statements. Most cells record an absence. Company figures are self-reported and mostly unaudited, and market-based emissions reflect contracts rather than the grid at the hour of use. Cite AI Safety Tracker, "Environmental Disclosure Index". https://aisafetytracker.org/environment/. Retrieved 24 October 2026.

The projections are the IEA's scenarios, and the dashed line joins the years it states without showing a path it publishes between them. The 2024 AI mark is the share of electricity used by accelerated servers, which the IEA uses as a proxy and calls imperfect. The 2030 mark is its AI-focused datacentres in the Base Case, and the 2025 level of that group is not stated in terawatt hours. The two marks are defined differently and are not joined. The 2035 range runs from 700 to 1,700 TWh across the IEA's four cases, and its text does not say which case sets which end. The April 2026 report restates the 2030 total as around 950 TWh.

Page: Environment

Datacentre power by country

AI datacentre capacity by country in Epoch AI's hub, and every datacentre's electricity by region in the IEA's estimate for 2024. The two measure different things.

AI datacentres, IT power by country Epoch AI's AI Data Centers hub: power operating on the retrieval date and planned at the last stage of each site's timeline, summed by the country Epoch records. AI Data Centers Epoch AI Licence CC-BY-4.0 Updated several times a week Retrieved , today The largest AI sites Epoch has found, mostly in the United States. Epoch estimated in September 2026 that they hold 44% of the world's deployed AI compute, with a 90% interval of 23% to 81%. Power, compute and cost are Epoch's estimates from satellite imagery, permits and company statements; four in five IT power estimates fall within a factor of 1.4 of the true value. The owner is the owner of the chips, not necessarily of the building. Capacity after the date of retrieval is Epoch's projection. Coordinates are read from the hub's map page, which publishes them; the downloads do not. Cite Epoch AI, "AI Data Centers". https://epoch.ai/data/ai-data-centers. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/. United States 33.1 GW of 38.2 GW planned
IT power of the AI datacentres in Epoch AI's hub by country, planned at each site's last stage and operating now, largest planned first. The hub holds 14.2 GW operating and 38.2 GW planned.
Country Planned Operating now Relative magnitude
United States 77 sites 33.1 GW 12 GW
China 5 sites 2.1 GW 731 MW
Malaysia 3 sites 1.1 GW 1.1 GW
United Arab Emirates 1 site 1 GW 0 MW
Portugal 1 site 233 MW 33 MW
Finland 1 site 145 MW 75 MW
Norway 2 sites 134 MW 42 MW
United Kingdom 1 site 88 MW 88 MW
Indonesia 1 site 72 MW 72 MW
Sweden 1 site 48 MW 0 MW
Show the remaining 2
IT power of the AI datacentres in Epoch AI's hub by country, planned at each site's last stage and operating now, largest planned first. The hub holds 14.2 GW operating and 38.2 GW planned. Rows 11 to 12.
Australia 1 site 41 MW 41 MW
Iceland 1 site 10.2 MW 5.1 MW
All datacentres, electricity by region, 2024 The shares are the IEA's, from Energy and AI (2025). The terawatt hours are those shares of the IEA's 2024 world total, multiplied here: the IEA states no regional figure in terawatt hours. Environmental Disclosure Index This site Licence MIT Updated quarterly Retrieved , 4 days ago Data 7 datasets Our own reading of what frontier developers and the operators of their data centres have published about training energy, emissions, power sources and energy per prompt, with permits and press reporting marked separately from company statements. Most cells record an absence. Company figures are self-reported and mostly unaudited, and market-based emissions reflect contracts rather than the grid at the hour of use. Cite AI Safety Tracker, "Environmental Disclosure Index". https://aisafetytracker.org/environment/. Retrieved 24 October 2026. 415 TWh world total
Share of world datacentre electricity in 2024 by region as the IEA states it, and the terawatt hours that share comes to.
Region Share of world TWh, computed
United States 45% 187
China 25% 104
Europe 15% 62
Rest of the world 15% 62

Power is the capacity a datacentre can draw and electricity is the energy it used, so the tables cannot be converted into each other: neither source states how fully the capacity is used. The hub holds 95 sites and is not a census of datacentres. Europe is the IEA's region and not the European Union. The rest of the world is the remainder after the three regions the IEA names, and includes Japan, for which it gives no share. Lawrence Berkeley National Laboratory states 192 TWh for the United States in 2024, 46% of the IEA's world total. Environmental Disclosure Index This site Licence MIT Updated quarterly Retrieved , 5 days ago Data 7 datasets Our own reading of what frontier developers and the operators of their data centres have published about training energy, emissions, power sources and energy per prompt, with permits and press reporting marked separately from company statements. Most cells record an absence. Company figures are self-reported and mostly unaudited, and market-based emissions reflect contracts rather than the grid at the hour of use. Cite AI Safety Tracker, "Environmental Disclosure Index". https://aisafetytracker.org/environment/. Retrieved 23 October 2026. AI Data Centers Epoch AI Licence CC-BY-4.0 Updated several times a week Retrieved , 5 days ago The largest AI sites Epoch has found, mostly in the United States. Epoch estimated in September 2026 that they hold 44% of the world's deployed AI compute, with a 90% interval of 23% to 81%. Power, compute and cost are Epoch's estimates from satellite imagery, permits and company statements; four in five IT power estimates fall within a factor of 1.4 of the true value. The owner is the owner of the chips, not necessarily of the building. Capacity after the date of retrieval is Epoch's projection. Coordinates are read from the hub's map page, which publishes them; the downloads do not. Cite Epoch AI, "AI Data Centers". https://epoch.ai/data/ai-data-centers. Retrieved 23 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Page: Environment

Training runs against published emissions

Every run since 2020 above 1.0e21 FLOP with a compute estimate, by developer, logarithmic scale. 1 of the 24 models at or above 1e25 FLOP has a published training-emissions figure.

1e211e221e231e241e251e261e271e25, EU thresholdOpenAIGPT-6 Astra (OpenAI, 2026-09): 9.4e26 FLOP, confidence Likely. No training emissions figure published.GPT-4.5 (OpenAI, 2025-02): 3.8e26 FLOP, confidence Likely. No training emissions figure published.GPT-5 (OpenAI, 2025-08): 6.6e25 FLOP, confidence Speculative. No training emissions figure published.GPT-4 (Mar 2023) (OpenAI, 2023-03): 2.1e25 FLOP, confidence Likely. No training emissions figure published.GPT-4 (Jun 2023) (OpenAI, 2023-06): 2.1e25 FLOP, confidence Likely. No training emissions figure published.gpt-oss-120b (OpenAI, 2025-08): 4.9e24 FLOP, confidence Confident. No training emissions figure published.GPT-3.5 (davinci-002) (OpenAI, 2022-03): 2.6e24 FLOP, confidence Speculative. No training emissions figure published.gpt-oss-20b (OpenAI, 2025-08): 5.5e23 FLOP, confidence Confident. No training emissions figure published.DALL·E 2 (OpenAI, 2022-04): 3.4e23 FLOP, confidence Speculative. No training emissions figure published.InstructGPT 175B (OpenAI, 2022-01): 3.2e23 FLOP, confidence Confident. No training emissions figure published.GPT-3 175B (davinci) (OpenAI, 2020-05): 3.1e23 FLOP, confidence Confident. Training emissions published.Codex (OpenAI, 2021-07): 7.3e22 FLOP, confidence Likely. No training emissions figure published.DALL-E (OpenAI, 2021-01): 4.7e22 FLOP, confidence Likely. No training emissions figure published.Statement Curriculum Learning (OpenAI, 2022-03): 1.8e22 FLOP, confidence Likely. No training emissions figure published.CLIP (ViT L/14@336px) (OpenAI, 2021-01): 1.0e22 FLOP, confidence Confident. No training emissions figure published.ADM (OpenAI, 2021-05): 6.2e21 FLOP, confidence Confident. No training emissions figure published.Whisper (OpenAI, 2022-09): 4.2e21 FLOP, confidence Likely. No training emissions figure published.GPT-6 AstraxAIGrok 4 (xAI, 2025-07): 5.0e26 FLOP, confidence Speculative. No training emissions figure published.Grok 3 (xAI, 2025-02): 3.5e26 FLOP, confidence Likely. No training emissions figure published.Grok-2 (xAI, 2024-08): 3.0e25 FLOP, confidence Confident. No training emissions figure published.Grok-1 (xAI, 2023-11): 2.9e24 FLOP, confidence Likely. No training emissions figure published.Grok 4MetaLlama 4 Behemoth (preview) (Meta, 2025-04): 5.2e25 FLOP, confidence Likely. No training emissions figure published.Llama 3.1-405B (Meta, 2024-07): 3.8e25 FLOP, confidence Confident. Training emissions published.Llama 3-70B (Meta, 2024-04): 7.9e24 FLOP, confidence Confident. Training emissions published.Llama 3.3 70B (Meta, 2024-12): 6.9e24 FLOP, confidence Confident. No training emissions figure published.Llama 4 Scout (Meta, 2025-04): 4.1e24 FLOP, confidence Likely. Training emissions published.Llama 4 Maverick (Meta, 2025-04): 2.2e24 FLOP, confidence Likely. Training emissions published.Movie Gen Video (Meta, 2024-10): 1.6e24 FLOP, confidence Confident. No training emissions figure published.Llama 2-70B (Meta, 2023-07): 8.1e23 FLOP, confidence Confident. Training emissions published.Llama 3.2 11B (Meta, 2024-09): 5.8e23 FLOP, confidence Confident. No training emissions figure published.LLaMA-65B (Meta, 2023-02): 5.5e23 FLOP, confidence Confident. No training emissions figure published.OPT-175B (Meta, 2022-05): 4.3e23 FLOP, confidence Confident. No training emissions figure published.Galactica (Meta, 2022-11): 3.2e23 FLOP, confidence Likely. No training emissions figure published.Llama Guard (Meta, 2023-12): 1.6e23 FLOP, confidence Confident. No training emissions figure published.Llama 2-7B (Meta, 2023-07): 8.4e22 FLOP, confidence Confident. No training emissions figure published.NLLB (Meta, 2022-07): 1.8e22 FLOP, confidence Confident. No training emissions figure published.Segment Anything Model (Meta, 2023-04): 7.8e21 FLOP, confidence Confident. No training emissions figure published.Make-A-Scene (Meta, 2022-03): 6.4e21 FLOP, confidence Likely. No training emissions figure published.Llama 4 Behemoth (preview)Google DeepMindGemini 1.0 Ultra (Google DeepMind, 2023-12): 5.0e25 FLOP, confidence Speculative. No training emissions figure published.PaLM 2 (Google DeepMind, 2023-05): 7.3e24 FLOP, confidence Likely. No training emissions figure published.Minerva (540B) (Google DeepMind, 2022-06): 2.7e24 FLOP, confidence Confident. No training emissions figure published.Flan-PaLM 540B (Google DeepMind, 2022-10): 2.5e24 FLOP, confidence Confident. No training emissions figure published.U-PaLM (540B) (Google DeepMind, 2022-10): 2.5e24 FLOP, confidence Confident. No training emissions figure published.Gopher (280B) (Google DeepMind, 2021-12): 6.3e23 FLOP, confidence Confident. No training emissions figure published.Chinchilla (Google DeepMind, 2022-03): 5.8e23 FLOP, confidence Confident. No training emissions figure published.FunSearch (Google DeepMind, 2023-12): 3.9e23 FLOP, confidence Speculative. No training emissions figure published.GLaM (Google DeepMind, 2021-12): 3.6e23 FLOP, confidence Confident. No training emissions figure published.LaMDA (Google DeepMind, 2022-02): 3.6e23 FLOP, confidence Confident. No training emissions figure published.AlphaCode (Google DeepMind, 2022-02): 2.4e23 FLOP, confidence Confident. No training emissions figure published.Flamingo (Google DeepMind, 2022-04): 2.2e23 FLOP, confidence Confident. No training emissions figure published.ViT-22B (Google DeepMind, 2023-02): 1.9e23 FLOP, confidence Confident. No training emissions figure published.PaLI (Google DeepMind, 2022-09): 1.7e23 FLOP, confidence Likely. No training emissions figure published.Switch (Google DeepMind, 2021-01): 8.2e22 FLOP, confidence Confident. No training emissions figure published.GShard (dense) (Google DeepMind, 2020-06): 4.8e22 FLOP, confidence Confident. No training emissions figure published.BASIC-L (Google DeepMind, 2021-11): 4.1e22 FLOP, confidence Likely. No training emissions figure published.Student of Games (Google DeepMind, 2021-12): 3.7e22 FLOP, confidence Speculative. No training emissions figure published.GOAT (Google DeepMind, 2021-07): 2.4e22 FLOP, confidence Speculative. No training emissions figure published.GraphCast (Google DeepMind, 2023-11): 2.1e22 FLOP, confidence Speculative. No training emissions figure published.RETRO-7B (Google DeepMind, 2022-02): 1.7e22 FLOP, confidence Confident. No training emissions figure published.FGN (Google DeepMind, 2025-06): 9.6e21 FLOP, confidence Confident. No training emissions figure published.ContextNet + Noisy Student (Google DeepMind, 2020-01): 8.2e21 FLOP, confidence Confident. No training emissions figure published.SigLIP 400M (Google DeepMind, 2023-03): 4.9e21 FLOP, confidence Confident. No training emissions figure published.Gato (Google DeepMind, 2022-05): 4.0e21 FLOP, confidence Confident. No training emissions figure published.AlphaFold 2 (Google DeepMind, 2020-11): 3.0e21 FLOP, confidence Likely. No training emissions figure published.Gemini 1.0 UltraAnthropicClaude 3.7 Sonnet (Anthropic, 2025-02): 3.4e25 FLOP, confidence Likely. No training emissions figure published.Claude 3.5 Sonnet (Anthropic, 2024-06): 2.7e25 FLOP, confidence Speculative. No training emissions figure published.Claude 2 (Anthropic, 2023-07): 3.9e24 FLOP, confidence Speculative. No training emissions figure published.Claude 3.7 SonnetDeepSeekDeepSeek-V4-Pro (DeepSeek, 2026-04): 9.7e24 FLOP, confidence Likely. No training emissions figure published.DeepSeek V4.1 Flash (DeepSeek, 2026-09): 4.3e24 FLOP, confidence Likely. No training emissions figure published.DeepSeek-R1 (May 2025) (DeepSeek, 2025-05): 4.0e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-R1 (DeepSeek, 2025-01): 3.5e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-V3 (DeepSeek, 2024-12): 3.3e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-V3 (Mar 2025) (DeepSeek, 2025-03): 3.3e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-V4-Flash (DeepSeek, 2026-04): 2.5e24 FLOP, confidence Likely. No training emissions figure published.DeepSeek-V2.5 (DeepSeek, 2024-09): 1.8e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-Coder-V2 236B (DeepSeek, 2024-06): 1.3e24 FLOP, confidence Confident. No training emissions figure published.DeepSeek-V4-ProMistral AIMixtral 8x7B (Mistral AI, 2023-12): 7.7e23 FLOP, confidence Speculative. No training emissions figure published.Mixtral 8x7BTraining compute, FLOP
Largest run per developer Other runs Ringed: emissions figure published Compute is Epoch AI's estimate. Whether emissions are published is this site's index. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , today Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/. Environmental Disclosure Index This site Licence MIT Updated quarterly Retrieved , today Data 7 datasets Our own reading of what frontier developers and the operators of their data centres have published about training energy, emissions, power sources and energy per prompt, with permits and press reporting marked separately from company statements. Most cells record an absence. Company figures are self-reported and mostly unaudited, and market-based emissions reflect contracts rather than the grid at the hour of use. Cite AI Safety Tracker, "Environmental Disclosure Index". https://aisafetytracker.org/environment/. Retrieved 28 October 2026.

Compute is the nearest measured quantity to training energy, not a measure of emissions. Compute figures are mostly Epoch AI's estimates.

Page: Environment

Safety research against capability research

Works indexed by OpenAlex per year by research area, logarithmic scale. In 2025, 14 works on safety, interpretability, evaluation or catastrophic risk for every 100 on frontier models; 330 in 2020.

1101001,00010,000100,0001,000,000201520172019202120232025Frontier model researchInterpretabilityGovernance and regulationSafety and alignmentEvaluation and red teamingCatastrophic and existential risk
Counts are a keyword match on title and abstract, not a field classification. The exact query for each series is listed on the page. OpenAlex OurResearch Licence CC0-1.0 Updated continuous Retrieved , today An open index of scholarly works. Counts here are matches on a stated search phrase in title or abstract, not a curated field classification: a paper that studies alignment without using the phrase is missed, and one that mentions it in passing is counted. The exact query behind every number is printed with it. Recent years undercount because indexing lags publication, and the current year is always partial. Cite OurResearch, "OpenAlex". https://openalex.org. Retrieved 28 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Counts are keyword matches on title and abstract, not a field classification; each query is printed on the page. The dashed line marks 2026, which is incomplete.

Page: Alignment

Releases against their system cards

Every release Epoch AI lists from the frontier developers since January 2025. 48 of 69 shipped with a system card on the day, 4 had one later and 17 have none.

OpenAI22 of 30 on the dayAnthropic15 of 15 on the dayGoogle DeepMind6 of 8 on the dayxAI1 of 6 on the dayMeta3 of 5 on the dayDeepSeek0 of 4 on the dayMicrosoft1 of 1 on the day
Card on the day Card published later No card Our own reading of each developer's publications, one release at a time. Release Safety Disclosure Index This site Licence MIT Updated monthly Retrieved , 10 days ago Data JSON CSV Our own reading of the system card, model card or safety report each developer published for each release Epoch AI lists from 2025, joined to Epoch's list. Every cell is what a developer says about its own model under its own framework: whether a card came out with the release, whether it reports dangerous-capability results, which government institutes it names as pre-release testers, and whether it says a risk threshold was reached. None of it is verified. A release Epoch adds after the last review is shown as awaiting review. Cite AI Safety Tracker, "Release Safety Disclosure Index". https://aisafetytracker.org/alignment/#releases. Retrieved 18 October 2026. Notable AI Models Epoch AI Licence CC-BY-4.0 Updated weekly Retrieved , 10 days ago Inclusion is editorial ("notability criteria"), not exhaustive. Compute figures are frequently estimates; check the per-row confidence and notes columns before treating any value as measured. Cite Epoch AI, "Notable AI Models". https://epoch.ai/data/ai-models. Retrieved 18 October 2026 via AI Safety Tracker, https://aisafetytracker.org/charts/.

Whether a card exists, and when it first appeared, is read from each developer's own publications. A card covering a model family counts for each model it names.

Page: Alignment

Tokens processed, as each company states it

Every aggregate token count a company has stated, converted to tokens per month, logarithmic scale. The largest is ByteDance, Doubao models at 5.5 quadrillion tokens a month in June 2026.

1 trillion10 trillion100 trillion1 quadrillion10 quadrillion202420252026ByteDance, Doubao models: 4 trillion tokens a day (December 2024), about 122 trillion a month. Volcano Engine FORCE conference.ByteDance, Doubao models: over 50 trillion tokens a day (December 2025), about 1.5 quadrillion a month. Volcano Engine FORCE conference.ByteDance, Doubao models: over 120 trillion tokens a day (March 2026), about 3.7 quadrillion a month. Volcano Engine statement.ByteDance, Doubao models: over 180 trillion tokens a day (June 2026), about 5.5 quadrillion a month. Volcano Engine FORCE conference.ByteDance, Doubao modelsGoogle, all products: 9.7 trillion tokens a month (April 2024), about 9.7 trillion a month. Google I/O keynote.Google, all products: over 480 trillion tokens a month (April 2025), about 480 trillion a month. Google I/O keynote.Google, all products: over 980 trillion monthly tokens (July 2025), about 980 trillion a month. Alphabet Q2 2025 earnings call.Google, all products: over 1.3 quadrillion monthly tokens (October 2025), about 1.3 quadrillion a month. Alphabet Q3 2025 earnings call.Google, all products: over 3.2 quadrillion tokens a month (May 2026), about 3.2 quadrillion a month. Google I/O keynote.Google, all productsGoogle, API only: 7 billion tokens per minute (October 2025), about 307 trillion a month. Alphabet Q3 2025 earnings call.Google, API only: over 10 billion tokens per minute (February 2026), about 438 trillion a month. Alphabet Q4 2025 earnings call.Google, API only: more than 16 billion tokens per minute (April 2026), about 701 trillion a month. Alphabet Q1 2026 earnings call.Google, API only: 22 billion tokens per minute (July 2026), about 964 trillion a month. Alphabet Q2 2026 earnings call.Google, API onlyOpenAI, API only: over 6 billion tokens per minute (October 2025), about 263 trillion a month. OpenAI DevDay keynote.OpenAI, API only: more than 15 billion tokens per minute (March 2026), about 657 trillion a month. OpenAI funding announcement.OpenAI, API onlyMicrosoft, Foundry: a record 50 trillion tokens last month (March 2025), about 50 trillion a month. Microsoft FY25 Q3 earnings call.Microsoft, Foundry: over 500 trillion this year (June 2025), about 42 trillion a month on average. Microsoft FY25 Q4 earnings call.Microsoft, Foundry
Google Other companies, by shade Dashed: API or platform only Hollow: average over a year Each point is a statement by the company. Per-minute and per-day rates converted to a month by this site. AI Usage Disclosure Index This site Licence MIT Updated quarterly Retrieved , 5 days ago Data 3 datasets Our own compilation of the token volumes, user counts and shares of use that companies and studies have put on the record, each linked to where it was stated. Scopes, units and token definitions differ between companies, so no two figures are comparable without the scope printed beside each. Figures known only through press reporting are marked as such. Not a market share estimate, and not a measure of any company's actual volume beyond what it chose to state. Cite AI Safety Tracker, "AI Usage Disclosure Index". https://aisafetytracker.org/usage/. Retrieved 23 October 2026.

No two series count the same thing, and each company uses its own tokeniser. A line joins only one company's figures for one scope.

Page: Usage

Law that applies to AI, by jurisdiction

86 instruments indexed in 11 jurisdictions. 48 are binding law, and 10 of those name AI in their own title.

European Union6 binding, 2 naming AISouth Korea3 binding, 2 naming AIChina7 binding, 2 naming AIUnited States6 binding, 2 naming AIJapan3 binding, 1 naming AIUnited Kingdom4 binding, 0 naming AICanada1 binding, 0 naming AIBrazil3 binding, 0 naming AIAustralia11 binding, 1 naming AIIndia3 binding, 0 naming AISingapore1 binding, 0 naming AI
Binding law Binds government Regulator guidance Voluntary Proposed or in review Our own index of primary legal instruments, tagged by how binding each is. AI Law and Policy Index This site Licence MIT Updated quarterly Retrieved , 5 days ago Data JSON CSV Our own reading of primary instruments, with a link to each. Not legal advice, not a compliance checklist and not exhaustive. Instruments that never mention AI are included where they apply to it, which is most of the Australian list. Statuses and commencement dates go stale; every record carries its review date. Cite AI Safety Tracker, "AI Law and Policy Index". https://aisafetytracker.org/policy/. Retrieved 23 October 2026.

Counts are of what this index lists, not of all law in force. Australia was indexed first and in more depth than the others.

Page: Policy