Google DeepMind
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 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 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 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.
| 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
| 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
| 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 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 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
| 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 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 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 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.
| 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 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 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.
| 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 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 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
- 0.24 Wh median text prompt, Gemini Apps, May 2025
- 100% of electricity matched with renewable purchases over 2025 , against 65% carbon-free hour by hour, as the company reports it
"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 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 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 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 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.