Google

Standalone agent-first platform announced at I/O 2026 (May 19), backed by Gemini 3.5 Flash. Comprises a desktop app, a Go-based Antigravity CLI (repla…

Launched at I/O 2026 (May 19) as the new default model in the Gemini app, AI Mode Search, and Antigravity 2.0. 1M-token context, configurable Thinking…

New Gemini model family launched at I/O 2026: image + audio + video + text in → video out. Distinct from the LLM-tier Gemini 3.5 Flash — po…

"AI Co-Mathematician: Accelerating Mathematicians with Agentic AI." Agentic-AI workbench from Google DeepMind that lets working mathematicians interle…

Position paper from Google DeepMind examining failure modes and risks of AI agents operating in real-world environments. By Matija Franklin, Nenad Tom…

4B-parameter medical multimodal model built on Gemma 3, trained for medical text and image comprehension. MedGemma 1.5 expands to high-dimensional med…

Four-variant family released under Apache 2.0 (a notable license upgrade from prior Gemma releases). Includes a 31B dense flagship, 26B-A4B MoE (4B ac…

Current flagship. 1M input, 65K output context. 2x+ reasoning boost over Gemini 3 Pro. "Medium" thinking parameter for latency/depth tradeoff. Leads 6…

"Olympiad-Level Formal Mathematical Reasoning with Reinforcement Learning." AlphaZero-inspired agent that learns to prove mathematical statements in L…

Gemini-powered evolutionary coding agent for scientific and algorithmic discovery. Found the first improvement to Strassen's matrix multiplication in…

First Gemini thinking model with built-in chain-of-thought reasoning. 1M token context. Led LMArena at launch. MoE architecture. Achieved SOTA on math…

First multimodal Gemma (vision + text). 128K token context (4B+). 140+ languages. Distilled training from larger Gemini models. Gemma-3-4B competitive…

Successor to BIG-Bench Hard (BBH), replacing its 23 saturated tasks with much harder variants designed to resist frontier model capabilities. Harmonic…

Demonstrates that looped Transformers — where a k-layer model is looped L times — can nearly match a kL-layer non-looped model on reasonin…

Probabilistic weather forecasting using diffusion models at 0.25° resolution. Outperformed ECMWF ENS on 97.2% of targets (99.8% at >36h lead ti…

Diffusion-based architecture predicting joint structures of proteins with DNA, RNA, small molecules, and ions. 50%+ improvement over existing methods…

Google's first open-weight models, built on Gemini research. 2B and 7B dense Transformers. Outperformed similarly sized open models on 11 of 18 text-b…

Sparse MoE Transformer with a breakthrough 1M token context window (up to 10M in research). Near-perfect recall (>99.7%) across the full context. E…

"Solving Olympiad Geometry without Human Demonstrations." Neuro-symbolic system that solves IMO geometry problems at near-gold-medal level (25 of 30 p…

ML-based weather forecasting using graph neural networks. 10-day forecasts at 0.25° resolution in under 1 minute on a single TPU v4. Outperformed ECMW…

First Gemini family: Ultra, Pro, and Nano tiers. Natively multimodal (text, image, audio, video). 32K token context. Ultra was the first model to surp…

"Scaling Deep Learning for Materials Discovery." Graph neural network that discovered 2.2 million new crystal structures, including 381,000 novel stab…

"Faster Sorting Algorithms Discovered Using Deep Reinforcement Learning." Used deep RL to discover novel sorting algorithms at the assembly instructio…

Introduced grouped-query attention as a middle ground between multi-head and multi-query attention, with a recipe for uptraining existing checkpoints…

"Fast Inference from Transformers via Speculative Decoding." Uses a small draft model to propose tokens verified in parallel by the large model, achie…

Pathways Language Model. 540B parameter dense Transformer trained on 6,144 TPU v4 chips using the Pathways system. 780B training tokens across multipl…

"Training Compute-Optimal Large Language Models." Found that existing LLMs were significantly undertrained: for compute-optimal training, model size a…

"Competition-Level Code Generation with AlphaCode." First AI to perform at a competitive level in programming contests. Achieved top 54.3% on Codeforc…

Showed that providing chain-of-thought reasoning demonstrations in prompts dramatically improves LLM performance on arithmetic, commonsense, and symbo…

"Finetuned Language Models Are Zero-Shot Learners." Instruction-tuned a 137B parameter model on 60+ NLP tasks described via natural language instructi…

Solved protein structure prediction at atomic accuracy. Won CASP14 with a median GDT score of 92.4 (next best: 73). Predicted structures for 200M+ pro…

Simplified Mixture-of-Experts routing for Transformers. Routes each token to a single expert (vs multiple in earlier MoE work), achieving 7x pre-train…

"An Image is Worth 16x16 Words." Applied a pure Transformer directly to sequences of image patches for classification, with no convolutional layers. A…

Composable transformations of Python+NumPy programs: automatic differentiation, vectorization, and JIT compilation to GPU/TPU via XLA. 35K+ GitHub sta…

Bidirectional Encoder Representations from Transformers. Pre-trained deep bidirectional representations by jointly conditioning on both left and right…

"Neural Discrete Representation Learning." Introduced Vector Quantised Variational AutoEncoder (VQ-VAE), which learns discrete latent representations…

The paper that introduced the Transformer architecture, dispensing with recurrence and convolutions entirely in favor of self-attention mechanisms. Mu…

First AI to defeat a human professional Go player. Combined deep neural networks with Monte Carlo tree search. Defeated European champion Fan Hui 5-0…

Open-source ML framework using dataflow graph computation, supporting CPUs, GPUs, and TPUs. 189K+ GitHub stars. Dominated deep learning research and p…

Introduced knowledge distillation: compressing a large "teacher" model into a smaller "student" by training on the teacher's soft probability distribu…

"Human-Level Control through Deep Reinforcement Learning." First deep learning agent to learn control policies directly from raw pixels via RL. Surpas…

"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift." Normalizes layer inputs during training, enabling much…