AI Safety Tracker

Google DeepMind

217 notable models 106 with a compute estimate Frontier Safety Framework

Google DeepMind has 217 models in Epoch AI's notable models list, 21 of them released since January 2025; the largest training run with a compute estimate is Gemini 1.0 Ultra, at 5.0e25 FLOP. Its published safety framework is the Frontier Safety Framework, and 6 of its 8 indexed releases since January 2025 had a safety card on the day of release.

  • 5.0e25 FLOP largest training run, Gemini 1.0 Ultra, 2023 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/developers/google-deepmind/.
  • 21 notable models released since January 2025
  • 6 of 8 releases since January 2025 with a system card on the day 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/developers/google-deepmind/.
  • 20 sites it owns in Epoch's data-centre hub

Models

Every model Epoch AI judges notable from Google DeepMind, by year, with the largest training run each year where Epoch has a compute estimate.

Notable models by year, with the largest training run each year.
Year Models Models, relative Largest run that year
2016 14 GNMT, 6.6e21 FLOP
2017 16 JFT, 8.4e20 FLOP
2018 14 Big Transformer for Back-Translation, 4.8e20 FLOP
2019 19 AlphaStar, 1.1e23 FLOP
2020 21 Meena, 1.1e23 FLOP
2021 22 FLAN 137B, 2.0e24 FLOP
2022 25 Minerva (540B), 2.7e24 FLOP
2023 25 Gemini 1.0 Ultra, 5.0e25 FLOP
2024 11 OpenVLA, 1.1e23 FLOP
2025 15 FGN, 9.6e21 FLOP
2026 6 WeatherNext 3, 2.1e23 FLOP

Most recent

Notable models, newest first.
Published Model Domain Released as Training compute
2026-09-30 Gemini 4 Argon Language Other -
2026-09-03 WeatherNext 3 Earth science API only 2.1e23
2026-09-02 Gemini 3.8 Flash Language API only -
2026-05-19 Gemini 3.5 Flash Language API only -
2026-04-15 Gemini Flash 3.1 TTS Audio API only -
2026-03-03 Gemini 3.0 Flash-lite Language API only -
2025-12-04 SIMA 2 3D modeling Unreleased -
2025-11-20 Gemini 3 Pro Image (Nano Banana Pro) Image generation API only -
2025-11-18 Gemini 3 Pro Multimodal API only -
2025-11-18 Gemini 3 Deep Think Language API only -
Earlier models 207
Notable models, newest first.
Published Model Domain Released as Training compute
2025-10-15 Veo 3.1 Video API only -
2025-09-25 Gemini Robotics-ER 1.5 Vision API only -
2025-08-26 Gemini 2.5 Flash Image (Nano Banana) Image generation API only -
2025-08-01 Gemini 2.5 Deep Think Language API only -
2025-07-14 Gemini Embedding Language API only -
2025-06-12 FGN Earth science Unreleased 9.6e21
2025-06-05 Gemini 2.5 Pro (Jun 2025) Language API only -
2025-05-21 Veo 3 Video API only -
2025-05-20 Imagen 4 Image generation API only -
2025-05-06 Gemini 2.5 Pro (May 2025) Language API only -
2025-03-25 Gemini 2.5 Pro (Mar 2025) Language API only -
2024-12-16 Veo 2 Video API only -
2024-12-11 Gemini 2.0 Pro Language API only -
2024-11-15 Gemini-Exp-1114 Language API only -
2024-09-05 AlphaProteo Biology Unreleased -
2024-08-07 Table Tennis Agent Robotics Unreleased -
2024-06-13 OpenVLA Robotics Open weights 1.1e23
2024-05-20 Octo-Base Robotics Open weights 5.8e20
2024-05-08 AlphaFold 3 Biology Open weights 4.1e22
2024-05-01 GenCast Earth science Open weights 8.2e20
2024-02-15 Gemini 1.5 Pro Language API only -
2024-01-17 AlphaGeometry Mathematics Open weights -
2023-12-23 GQA-8-XXL Language Unreleased 3.5e22
2023-12-19 Gemini Nano-2 Multimodal Unreleased -
2023-12-19 Gemini Nano-1 Multimodal API only -
2023-12-14 FunSearch Language Open weights 3.9e23
2023-12-11 W.A.L.T Video Unreleased -
2023-12-06 Gemini 1.0 Ultra Multimodal API only 5.0e25
2023-12-06 Gemini 1.0 Pro Multimodal API only -
2023-11-29 GNoME for crystal discovery Materials science Unreleased -
2023-11-14 GraphCast Earth science Open weights 2.1e22
2023-11-03 RT-Trajectory Robotics Unreleased -
2023-10-17 PaLI-3 Multimodal Unreleased -
2023-10-13 RT-2-X Robotics Unreleased -
2023-09-22 AlphaMissense Biology Unreleased -
2023-07-28 RT-2 Robotics Unreleased -
2023-07-26 AudioLM Audio Unreleased 3.9e18
2023-05-29 PaLI-X Multimodal Unreleased 5.6e23
2023-05-16 Med-PaLM 2 Medicine Unreleased -
2023-05-10 PaLM 2 Language API only 7.3e24
2023-04-26 Agile Soccer Robot Robotics Unreleased -
2023-03-27 SigLIP 400M Vision Open weights 4.9e21
2023-03-06 PaLM-E Robotics Unreleased -
2023-02-13 BASIC-L + Lion Vision Unreleased -
2023-02-10 ViT-22B Vision Unreleased 1.9e23
2023-01-26 MusicLM Audio Unreleased -
2023-01-10 DreamerV3 Games Unreleased 2.2e20
2022-12-13 RT-1 Robotics Open weights -
2022-12-01 DeepNash Games Unreleased -
2022-11-03 Mogrifier RLSTM (WT2) Language Unreleased 1.4e17
2022-10-20 U-PaLM (540B) Language Unreleased 2.5e24
2022-10-20 LMSI-Palm Language Unreleased -
2022-10-20 Flan-PaLM 540B Language Unreleased 2.5e24
2022-10-05 Phenaki Video Unreleased -
2022-10-05 AlphaTensor Other Unreleased 7.1e20
2022-09-14 PaLI Language Unreleased 1.7e23
2022-06-29 Minerva (540B) Language Unreleased 2.7e24
2022-06-22 Parti Image generation Unreleased 5.1e23
2022-06-14 CoCa Vision Unreleased 7.3e22
2022-05-23 Imagen Image generation API only 1.5e22
2022-05-12 Gato Multimodal Unreleased 4.0e21
2022-05-10 UL2 Language Open weights 1.2e23
2022-04-29 Flamingo Multimodal Unreleased 2.2e23
2022-04-14 XMC-GAN Image generation Unreleased -
2022-04-04 PaLM (540B) Language Unreleased 2.5e24
2022-03-29 Chinchilla Language Unreleased 5.8e23
2022-03-10 ViT-G (model soup) Vision Open weights 3.4e21
2022-02-17 ST-MoE Language Unreleased 2.9e23
2022-02-10 LaMDA Language Unreleased 3.6e23
2022-02-08 MaskGIT (ImageNet) Image generation Not recorded -
2022-02-07 RETRO-7B Language Unreleased 1.7e22
2022-02-02 AlphaCode Language Unreleased 2.4e23
2021-12-15 LongT5 Language Open weights -
2021-12-13 GLaM Language Unreleased 3.6e23
2021-12-08 Gopher (280B) Language Unreleased 6.3e23
2021-12-06 Student of Games Games Unreleased 3.7e22
2021-11-19 BASIC-L Vision Unreleased 4.1e22
2021-11-15 ViT-G/14 (LiT) Vision Unreleased -
2021-10-04 AlphaFold-Multimer Biology Open weights 4.3e21
2021-09-03 FLAN 137B Language Unreleased 2.0e24
2021-08-07 W2v-BERT Speech Unreleased -
2021-07-27 GOAT Games Unreleased 2.4e22
2021-06-23 EfficientNetV2-XL Vision Open weights 9.6e19
2021-06-11 ALIGN Multimodal Unreleased 2.6e22
2021-06-09 EMDR Language Open weights 1.9e21
2021-06-09 CoAtNet Vision Unreleased 4.3e22
2021-06-08 ViT-G/14 Vision Unreleased 5.8e22
2021-05-28 ByT5-XXL Language Open weights 8.1e22
2021-05-26 Transformer local-attention (NesT-B) Vision Open weights 2.4e19
2021-05-04 ProtT5-XL-U50 Biology Open weights 1.9e22
2021-05-04 ProtBERT-BFD Biology Open weights 3.9e22
2021-03-01 Meta Pseudo Labels Vision Unreleased 4.8e22
2021-01-11 Switch Language Open weights 8.2e22
2021-01-10 BigSSL Speech Unreleased -
2020-12-25 CT-MoS (WT2) Language Unreleased 5.4e17
2020-11-30 AlphaFold 2 Biology Open weights 3.0e21
2020-10-22 ViT-Huge/14 Vision Open weights 4.3e21
2020-10-22 ViT-Base/32 Vision Open weights -
2020-10-20 mT5-XXL Language Open weights 8.2e22
2020-10-20 Conformer + Wav2vec 2.0 + Noisy Student Speech Unreleased 7.6e21
2020-07-27 EfficientDet Vision Open weights -
2020-06-30 GShard (dense) Language Unreleased 4.8e22
2020-05-16 Conformer Speech Unreleased -
2020-05-07 ContextNet Speech Unreleased -
2020-03-30 Agent57 Games Unreleased -
2020-03-24 MetNet Earth science Unreleased 9.5e18
2020-03-23 ELECTRA Language Open weights 3.1e21
2020-03-12 Routing Transformer (WT-103) Language Open weights -
2020-02-14 FFN SwiGLU Language Unreleased 3.4e19
2020-02-13 SimCLR Vision Open weights -
2020-02-09 ALBERT-xxlarge Language Open weights 2.4e21
2020-02-08 Perceiver IO (optical flow) Multimodal Unreleased -
2020-01-28 Meena Language Unreleased 1.1e23
2020-01-19 ContextNet + Noisy Student Speech Unreleased 8.2e21
2020-01-15 AlphaFold Biology Unreleased 1.0e20
2019-12-24 Big Transfer (BiT-L) Vision Unreleased -
2019-11-19 MuZero Games Unreleased 4.8e19
2019-11-11 Noisy Student (L2) Vision Unreleased 2.6e22
2019-10-30 AlphaStar Games Unreleased 1.1e23
2019-10-23 T5-11B Language Open weights 3.3e22
2019-10-23 T5-3B Language Open weights 9.0e21
2019-10-11 M4-50B Language Unreleased -
2019-09-26 ALBERT Language Open weights -
2019-09-04 Mogrifier (d2, MoS2, MC) + dynamic eval Language Unreleased -
2019-07-04 BigBiGAN Vision Open weights -
2019-06-19 Walking Minotaur robot Robotics Unreleased -
2019-06-01 XLNet Language Open weights 6.2e21
2019-05-28 EfficientNet-L2 Vision Open weights -
2019-05-22 CPC v2 Vision Unreleased -
2019-04-26 Neuro-Symbolic Concept Learner Vision Unreleased -
2019-02-28 NMT Transformer 437M Language Unreleased -
2019-02-09 SDE Language Unreleased -
2019-02-01 Hanabi 4 player Games Unreleased 4.3e18
2019-01-09 Transformer-XL (257M) Language Open weights 3.8e20
2018-12-04 SPN (ImageNet 128) Image generation Unreleased -
2018-11-16 GPipe (Transformer) Language Not recorded -
2018-11-05 Mesh-TensorFlow Transformer 4.9B (language) Language Unreleased 1.6e20
2018-11-05 Mesh-TensorFlow Transformer 2.9B (translation) Language Unreleased 6.8e19
2018-10-11 MetaMimic Robotics Not recorded -
2018-10-11 BERT-Large Language Open weights 2.9e20
2018-09-17 Transformer + Simple Recurrent Unit Language Unreleased 1.1e19
2018-08-28 Big Transformer for Back-Translation Language Open weights 4.8e20
2018-07-03 FTW (For The Win) Games Unreleased 3.5e19
2018-06-18 MobileNetV2 Vision Not recorded -
2018-06-05 Relational Memory Core Language Unreleased -
2018-02-07 DeepLabV3+ Vision Not recorded -
2018-02-05 IMPALA Games Unreleased 1.7e20
2018-01-30 T-DMCA Language Unreleased -
2017-12-05 AlphaZero Games Unreleased 1.1e20
2017-11-02 VQ-VAE Vision Unreleased -
2017-10-19 AlphaGo Master Games Unreleased 3.4e20
2017-10-18 AlphaGo Zero Games Unreleased 6.5e20
2017-10-06 Rainbow DQN Games Unreleased -
2017-07-21 NASNet-A Vision Not recorded -
2017-07-18 AWD-LSTM Language Unreleased -
2017-07-10 JFT Vision Not recorded 8.4e20
2017-06-30 NoisyNet-Dueling Games Unreleased -
2017-06-17 DeepLabV3 Vision Not recorded -
2017-06-12 Transformer Language Unreleased 7.4e18
2017-06-08 Reading Twice for NLU Language Not recorded -
2017-06-01 Inflated 3D ConvNet 3D modeling Not recorded -
2017-04-27 DeepLab (2017) Vision Not recorded -
2017-04-17 MobileNet Vision Not recorded -
2017-01-23 MoE-Multi Language Unreleased 9.4e19
2016-12-02 Elastic weight consolidation Vision Not recorded -
2016-11-05 NASv3 (CIFAR-10) Vision Not recorded 2.2e21
2016-11-05 NAS with base 8 and shared embeddings Language Unreleased 1.1e16
2016-10-07 Xception Vision Not recorded 4.4e20
2016-09-26 GNMT Language API only 6.6e21
2016-09-15 Youtube recommendation model Recommendation Not recorded -
2016-09-12 WaveNet Speech Not recorded -
2016-06-16 PixelCNN Vision Not recorded -
2016-04-05 Dueling DQN Games Unreleased -
2016-03-02 Double DQN Games Unreleased -
2016-02-23 Inceptionv4 Vision Not recorded -
2016-02-23 Inception-ResNet-V2 Vision Not recorded -
2016-02-04 A3C FF hs Games Not recorded -
2016-01-27 AlphaGo Lee Games Unreleased 1.9e21
2015-12-15 Advantage Learning Games Not recorded -
2015-12-02 Inception v3 Vision Not recorded 1.0e20
2015-10-01 AlphaGo Fan Games Unreleased 3.8e20
2015-09-09 Deep Deterministic Policy Gradients Robotics Not recorded -
2015-06-15 BatchNorm Vision Not recorded -
2015-02-25 DQN-2015 Games Not recorded -
2014-12-03 SNM-skip Language Not recorded 3.0e20
2014-09-17 GoogLeNet / InceptionV1 Vision Not recorded 1.5e18
2014-09-10 Seq2Seq LSTM Language Not recorded 5.6e19
2014-06-23 Multiresolution CNN Video Not recorded -
2014-06-22 RNN-WER Speech Not recorded -
2014-05-14 Paragraph Vector Language Not recorded -
2013-12-19 DQN Games Not recorded 2.8e15
2013-12-11 RNN for 1B words Language Not recorded -
2013-12-05 TransE Language Not recorded 1.3e18
2013-12-05 DeViSE Vision Not recorded -
2013-10-16 Word2Vec (small) Language Not recorded -
2013-10-16 Word2Vec (large) Language Not recorded 3.9e16
2013-05-26 ReLU-Speech Speech Not recorded 1.3e17
2013-05-26 Multilingual DNN Speech Not recorded -
2013-01-16 DistBelief NNLM Language Not recorded 2.6e18
2012-12-03 DistBelief Vision Vision Not recorded -
2012-12-03 DistBelief Speech Speech Not recorded 3.1e17
2012-07-12 Unsupervised High-level Feature Learner Vision Not recorded 6.0e17
2011-10-03 Adaptive Subgrad Language Not recorded -
2011-06-19 Cross-Lingual POS Tagger Language Not recorded -
2010-09-26 YouTube Video Recommendation System Recommendation Not recorded -
2007-06-22 SB-LM Language Not recorded 1.4e18
2007-06-22 KN-LM Language Not recorded 7.7e17

Notability is Epoch's editorial judgement, and compute figures are its estimates, most of them not disclosed by the developer. Includes models Epoch credits to Google, Google Brain, Google Research and DeepMind before they merged, and Google's own statements and sites. 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/developers/google-deepmind/. 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/developers/google-deepmind/.

Safety framework and release disclosures

The frontier safety framework Google DeepMind has published, and what it published at each release since January 2025.

Framework
Frontier Safety Framework since 2024
Its own scale
Critical Capability Levels per domain, with lower Tracked Capability Levels for some
Risk domains
CBRN, cyber, manipulation, AI R&D, loss of control
External evaluation
not stated
Commits to stop
qualified: Commits to a decision process rather than to an outcome.

Version 3.1 took effect on 17 April 2026. Adds Tracked Capability Levels below the critical ones, for CBRN and for a domain that now merges machine-learning R&D with misalignment. Risk acceptance weighs what other publicly available models can do, and for misuse risks applies to external deployment only, not to internal use or further development.

  • 6 of 8 with a system card on the day
  • 0 that no card names
  • 0 naming a government institute that tested before release
  • 2 stated to have reached a threshold in its own framework
Google DeepMind releases since January 2025, with the card published for each.
Released Model Card Results Government tested Threshold
2026-09-30 Gemini 4 Argon Released to trusted cyber defenders on 30 September; the card followed on 13 October. The launch post mentions the US government's voluntary pre-release access process and names no institute. 13 days later results none named reached CBRN and cybersecurity CCLs could not be ruled out; safety cases applied
2026-09-02 Gemini 3.8 Flash at release another model's none named below Relies on Gemini 3.7 Flash, which reached no Tracked or Critical Capability Level
2026-05-19 Gemini 3.5 Flash at release another model's none named below Relies on Gemini 3.1 Pro, which reached no CCL
2026-03-03 Gemini 3.0 Flash-lite Epoch lists it as Gemini 3.0 Flash-lite and links Google's announcement of Gemini 3.1 Flash-Lite. at release another model's none named below Relies on Gemini 3.1 Pro with Deep Think, which reached no CCL
2025-11-18 Gemini 3 Pro at release results none named below No CCL reached; alert threshold met for cybersecurity
2025-11-18 Gemini 3 Deep Think The Gemini 3 Pro card reports its evaluations of Deep Think mode as consistent with Gemini 3 Pro's. at release results none named below No CCL reached
2025-08-01 Gemini 2.5 Deep Think at release results none named reached At the alert threshold for CBRN Uplift Level 1; further mitigations applied as a precaution
2025-03-25 Gemini 2.5 Pro (Mar 2025) The first card, for the preview, appeared 23 days after release. The linked card is its current version. 23 days later results none named below No CCL reached; alert threshold reached for Cyber Uplift Level 1

Every entry is Google DeepMind's own statement about its own models under its own framework. The rules behind each column are on the alignment page. Frontier Safety Framework Index This site Licence MIT Updated quarterly Retrieved , 10 days ago Data JSON CSV Our own reading of each developer's published safety framework and model cards. Every field is what the developer says about itself: these are self-assessments under self-written frameworks with no common scale and no external audit, and they are indexed here for exactly that reason. Not a ranking, and not a verification. Cite AI Safety Tracker, "Frontier Safety Framework Index". https://aisafetytracker.org/alignment/#frameworks. Retrieved 18 October 2026. 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/developers/google-deepmind/.

Its models against the compute thresholds

How many of Google DeepMind's models with a compute estimate sit at or above each training-compute threshold written into an instrument, and the first to cross it.

Training-compute thresholds and this developer's models above each.
Instrument Threshold Status Its models above First of them to cross
Regulation (EU) 2024/1689, Article 51(2) European Union 1e25 in force 1 Gemini 1.0 Ultra, 2023-12-06
SB 53, Transparency in Frontier Artificial Intelligence Act United States (California) 1e26 in force 0 -
Enforcement Decree of the AI Basic Act, Article 23 South Korea 1e26 in force 0 -
Executive Order 14110, section 4.2 United States (federal) 1e26 revoked 0 -
SB 1047, Safe and Secure Innovation for Frontier AI Models Act United States (California) 1e26 vetoed 0 -
RAISE Act, Responsible AI Safety and Education Act United States (New York) 1e26 enacted 0 -

Arithmetic on Epoch's compute estimates against the number in each instrument, not a legal finding about any model. The full timeline is on the capability page. 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/developers/google-deepmind/.

Datacentres

Sites in Epoch AI's data-centre hub that Google DeepMind owns or is named as using, largest planned IT power first. Those it owns plan 5.9 GW of IT power between them.

Datacentre sites this developer owns or uses, with power now and planned.
Site Role Country Stage IT power now Planned
Goodnight owner, speculative United States Under construction - 1.0 GW
Google Fort Wayne owner, confident United States Under construction - 863 MW
Google Omaha owner, confident United States Expanding 237 MW 395 MW
Google Columbus owner, confident United States Expanding 303 MW 386 MW
Google Pryor (North) owner, confident United States Operating 368 MW 368 MW
Google New Albany owner, confident United States Operating 333 MW 333 MW
Google Storey County owner, confident United States Expanding 161 MW 300 MW
Google Lincoln owner, confident United States Expanding 141 MW 283 MW
Google Cedar Rapids owner, confident United States Under construction - 261 MW
Google Bristow owner United States Operating 238 MW 238 MW
Google Council Bluffs (East) owner, confident United States Operating 237 MW 237 MW
Google Papillion owner, confident United States Operating 237 MW 237 MW
Google Mesa owner, confident United States Operating 183 MW 183 MW
Google Red Oak owner, confident United States Expanding 77 MW 154 MW
Google The Dalles owner, confident United States Operating 154 MW 154 MW
Google Lancaster owner, confident United States Operating 137 MW 137 MW
Google Kansas City East owner, confident United States Operating 105 MW 105 MW
Google Midlothian owner, confident United States Operating 103 MW 103 MW
Google Waltham Cross owner, confident United Kingdom Operating 88 MW 88 MW
Google Arcola owner, confident United States Operating 77 MW 77 MW

Power is Epoch's estimate from imagery and permits, IT power where it states one. Confidence is Epoch's own label for each owner or user. 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/developers/google-deepmind/. AI Datacentre Index This site Licence MIT Updated quarterly Retrieved , today 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 28 October 2026.

Energy and emissions

What Google DeepMind has published about the energy behind its models, and what permits and press reporting add.

Training energy or emissions Not disclosed
No energy or emissions figure for any Gemini model. The Gemma 3 model card no longer carries the pre-training figure it once gave.
Where it trains and serves Partly published
Google's own data centres. Which sites train or serve a given model is not stated. Google
What powers those sites Published
65% carbon-free energy hour by hour across Google's data centres in 2025, and 100% matched with renewable purchases over the year. Google
Energy per prompt Published
0.24 Wh, 0.03 gCO2e and 0.26 mL of water for the median Gemini Apps text prompt, May 2025, with a published method. Google

"Published" means the developer's own statement; "reported by others" means a permit, a regulator or the press. A company's clean-energy claims cover its whole operation, never one model. 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. 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.

Usage

The token volumes and user counts Google DeepMind has stated, each in its own scope.

  • 3.2 quadrillion tokens a month, Google, all products, as of May 2026 source
  • 964 trillion tokens a month, Google, API only, as of July 2026 source
  • 2.5 billion monthly users, Google AI Overviews, as of May 2026 source
  • 1 billion monthly users, Google AI Mode, as of May 2026 source
  • 950 million monthly users, Gemini app, as of July 2026 source

Volumes are normalised to a month and are comparable only within one company's own scope. Every series with its scope is on the usage page. 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. 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.