Google DeepMind
Profile Overview
Google DeepMind is the consolidated artificial intelligence research unit of Google, established in April 2023 by merging the London-based DeepMind company with Google's Brain team. Originally founded in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman, DeepMind was acquired by Google in 2014 for approximately $500 million. Since its inception, DeepMind has pioneered major milestones in reinforcement learning, famously developing AlphaGo, which defeated world champion Lee Sedol in the game of Go in 2016. The team also created AlphaFold, a revolutionary system that predicts 3D protein structures with atomic accuracy, solving a 50-year-old biological challenge and accelerating global medical research. Today, Google DeepMind leads the development of Google's flagship Gemini models, a multimodal series natively designed to process text, code, audio, video, and images. Google DeepMind's research underpins many Google consumer and enterprise products, including Search, Android, and Google Cloud Vertex AI. Although operating under Alphabet, its internal corporate standing represents a premier AI powerhouse valued at over $100 billion. The unit remains committed to advancing the frontier of artificial general intelligence responsibly, combining scientific rigor with Google's massive computing infrastructure to deliver breakthroughs across computer science, materials science, and biochemistry.
Last Financing Round
Flagship Offerings
Vetted AI Models
Gemini 3.5 Flash
activeGoogle's latest high-speed, high-efficiency model, featuring a large context window and multimodality.
Gemini 3.1 Pro
activeGoogle's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.
Gemini 3.1 Flash
activeOur high-speed, cost-efficient model. Features a 1 million token context window, optimized for high-volume content synthesis, classification, and routing.
Gemini 2.5 Pro
activePrevious-generation professional model featuring the 2 million context length, optimized for large file processing and code reasoning.