Google

Updated June 2026

Google is the maker of Gemini and the only AI company with a full owned stack — frontier models from Google DeepMind, its own TPU chips, Google Cloud, and distribution through Search, Android, Chrome and Workspace. After being caught off-guard by ChatGPT, it has staged a comeback: the Gemini app passed 900 million monthly users in 2026 and Google Cloud is its fastest-growing business.

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Google is the maker of Gemini and the only AI company that owns its entire stack: frontier models from Google DeepMind, its own TPU chips, Google Cloud to serve them, and unrivalled distribution through Search, Android, Chrome, YouTube and Workspace. Google invented the transformer architecture behind modern AI in 2017, was caught flat-footed by ChatGPT in 2022, and has since staged a comeback — the Gemini app passed 900 million monthly active users by Google I/O in May 2026, up from 400 million a year earlier (TechCrunch).

The 2026 story is that Google’s full-stack advantage is paying off commercially. Google Cloud is now its fastest-growing business, AI is its primary cloud growth driver, and Alphabet is spending $180–190 billion on AI infrastructure for the year. Google’s TPUs have become a genuine alternative to Nvidia — enough that rival Anthropic signed a deal for up to $40 billion of Google compute. The overhang is legal: Google faces the most aggressive US antitrust action since Microsoft in the 1990s, with remedies now reaching into its AI products.

Quick facts

History and founding

Google was founded in 1998 by Larry Page and Sergey Brin. Its researchers published “Attention Is All You Need” in 2017, inventing the transformer — the architecture behind virtually every modern large language model, including those of its rivals. Despite that head start, OpenAI’s November 2022 launch of ChatGPT caught Google off-guard; the company declared an internal “code red,” and a botched 2023 demo of its Bard chatbot wiped roughly $100 billion off the stock in a day.

The turnaround began with structure. In April 2023 Google merged DeepMind and Google Brain into a single division, Google DeepMind, under Demis Hassabis, and focused it on the Gemini family launched that December. By 2026 Google had reorganised further, folding the Gemini product team into DeepMind to tighten the research-to-product loop.

Google DeepMind and structure

Google’s AI is built by Google DeepMind, led by co-founder and Nobel laureate Demis Hassabis (whose AlphaFold work won a share of the 2024 Nobel Prize in Chemistry). It sits inside Alphabet Inc., the holding company, with Sundar Pichai as CEO of both Alphabet and Google and Koray Kavukcuoglu as DeepMind’s CTO and Google’s Chief AI Architect. The 2026 consolidation of the Gemini team into DeepMind, plus changes in Search leadership, reflect how central AI has become to the whole company.

The full-stack advantage: models, chips and cloud

Google’s defining edge is that it owns every layer of the AI stack, which no other frontier lab does:

• Models — the Gemini family (and open-weight Gemma), built by Google DeepMind.
• Chips — Google’s own Tensor Processing Units (TPUs). The seventh-generation Ironwood is built for large-scale inference, an eighth generation is previewed on TSMC’s 2nm process, and Google projects roughly 4.3 million TPUs shipped in 2026, rising sharply thereafter — making it the only credible alternative to Nvidia at scale.
• Cloud — Google Cloud and Vertex AI to train, host and sell the models.
• Distribution — Search (billions of users), Android, Chrome, YouTube, Pixel and Workspace.

This vertical integration lets Google control cost and supply end to end, and it is why rivals now buy Google’s compute (see the Anthropic deal below).

Models and the Gemini line

Google ships Gemini on a Pro/Flash cadence, plus a Deep Think reasoning mode and the open-weight Gemma line. Live benchmarks for each model render in the table below this page.

The current generally-available flagship is Gemini 3.1 Pro. Gemini 3.5 Pro — targeting a 2M-token context window, Deep Think reasoning and frontier multimodal — was announced at Google I/O on 19 May 2026 but slipped (“give us until next month,” in Sundar Pichai’s words) and remains in limited Vertex preview as of mid-June 2026, not yet widely available (Tech Times). Google also ships Gemini 3 Deep Think (extended reasoning), the Gemma 4 open-weight models, and dedicated media models — Veo for video, Imagen for images, and the “Nano Banana” image-editing model. Gemini’s signature strengths are its very large context windows and native multimodality. See best AI models for where the lineup ranks; vendor numbers are a ceiling and standardised leaderboards a floor.

Products and ecosystem

• Gemini app — the consumer assistant (web, Android, iOS), 900M+ monthly users, with free, Google AI Pro ($19.99/mo) and Google AI Ultra ($99.99/mo, cut from $249.99) tiers.
• AI in Search — AI Overviews reach about 2 billion monthly users, and AI Mode (a conversational, multimodal search experience) reached tens of millions of daily users — described by Google as its biggest Search change in 25 years.
• Gemini in Workspace — built into Gmail, Docs, Sheets, Meet and the rest of Workspace.
• Vertex AI and the Gemini API / Google AI Studio — the enterprise and developer platforms.
• Agents and tools — Project Astra (live multimodal assistant), Project Mariner (web agent), and NotebookLM.
• On-device and hardware — Gemini Nano on Pixel and Android, and deep Pixel integration.

Business and financials

Alphabet reported Q1 2026 revenue of $109.9 billion, up 22% year on year — its fastest growth in two years — with net income up about 81% (CNBC). The standout is cloud: Google Cloud passed $20 billion in the quarter, up roughly 63%, with backlog near $460 billion, and Pichai told analysts that enterprise AI had become the primary cloud growth driver for the first time. Alphabet guided to $180–190 billion of capital expenditure in 2026, almost all of it AI infrastructure. Search advertising remains the profit engine that funds the AI build-out.

The Anthropic deal and compute strategy

In a striking sign of its chip strength, Google agreed in April 2026 to invest up to $40 billion in Anthropic in cash and compute, locking in around 5 gigawatts of TPU capacity for the Claude maker and backstopping its lease payments — effectively underwriting a ~$35 billion chip commitment (CNBC, Bloomberg). It is the largest commitment to an AI startup outside Microsoft’s OpenAI partnership, and it shows Google playing both sides — competing with Anthropic on models while selling it the compute to train them.

Leadership

• Sundar Pichai — CEO of Alphabet and Google.
• Demis Hassabis — CEO and co-founder of Google DeepMind; 2024 Nobel laureate (Chemistry, for AlphaFold).
• Koray Kavukcuoglu — CTO of Google DeepMind and Chief AI Architect at Google, reporting to Pichai.
• Ruth Porat — President and Chief Investment Officer (former CFO).

Competition and market position

Google competes with OpenAI and Anthropic at the model frontier, with Microsoft in enterprise AI, and with Amazon and Microsoft in cloud. Its unique position is the full stack: it is the only rival that makes its own frontier models and its own chips and runs a hyperscale cloud and owns mass-market distribution. That lets it absorb AI into products billions already use — Search, Android, Workspace — rather than having to win new audiences.

On models, Gemini is genuinely frontier-class, strongest on long context and multimodal breadth, though Anthropic leads the hardest coding benchmarks and OpenAI leads consumer reach. Google’s pressure points are turning its enormous usage into the same per-user monetisation rivals see, shipping flagships on time (Gemini 3.5 Pro slipped), and the antitrust overhang.

Controversies

• Antitrust. Google faces the most aggressive US antitrust action since Microsoft in the 1990s. In the search-monopoly case it must end exclusive default-search agreements by mid-2026, and remedies have been extended to its generative-AI products to stop search-era tactics carrying into AI; a separate ad-tech case and a Chrome-divestiture fight are also live.
• AI Overviews accuracy. AI-generated answers in Search have drawn criticism for confident errors and for diverting traffic from publishers.
• Image-generation history. Google’s 2024 Gemini image generator was pulled after producing historically inaccurate images, a reputational episode it has worked to move past.
• Energy and capex. The ~$180–190 billion capex and the data-centre energy footprint draw scrutiny over cost and sustainability.

Recent developments (2026)

• Gemini app passed 900 million monthly users (Google I/O, May 2026), up from 400 million a year earlier.
• Gemini 3.1 Pro went generally available (February); Gemini 3.5 Flash shipped at I/O (May); Gemini 3.5 Pro was announced but slipped to a limited June rollout.
• $40 billion Anthropic deal (April) committed Google TPU compute to a direct model rival.
• Google Cloud accelerated to ~63% growth, with enterprise AI the primary driver.
• Antitrust remedies began taking effect, including the end of exclusive default-search deals and AI-product provisions.

Where Google excels

• Full-stack control. Owns models, TPUs, cloud and distribution — no rival matches all four.
• Distribution. Search, Android, Chrome, YouTube and Workspace put Gemini in front of billions.
• Long context and multimodal. Gemini leads on very large context windows and native multimodality, with Veo and Imagen for media.
• Compute economics. Its own TPUs lower cost and reduce Nvidia dependence — and are now sold to rivals.

Where Google falls short

• Monetisation per user. Huge reach has not yet converted to rivals’ per-user revenue, and AI risks cannibalising lucrative search ads.
• Shipping cadence. Gemini 3.5 Pro slipping after its I/O announcement underlined execution pressure at the frontier.
• Coding leadership. On the hardest coding benchmarks, Claude leads Gemini.
• Legal overhang. Antitrust remedies now reaching AI products are a structural risk no rival faces to the same degree.

Developer resources

Google’s developer stack centres on the Gemini API via Google AI Studio (fast prototyping, free tier) and Vertex AI (enterprise deployment, tuning, governance), spanning the Gemini Pro/Flash models, Gemma open weights, and the Veo and Imagen media models. Models run on Google’s own TPUs, and Gemini is embedded across Workspace, Android (Gemini Nano) and Firebase. Pricing is on the Gemini API pricing page; Cloud status is at status.cloud.google.com.

Frequently asked questions

Is Gemini made by Google or DeepMind?

Both — Google DeepMind is Google’s AI division, and it builds the Gemini models. Google DeepMind was formed in 2023 by merging DeepMind and Google Brain, is led by co-founder Demis Hassabis, and sits inside Alphabet alongside the rest of Google.

What is Google’s latest AI model?

The generally-available flagship is Gemini 3.1 Pro. Gemini 3.5 Pro — targeting a 2M-token context window and Deep Think reasoning — was announced at Google I/O in May 2026 but, as of mid-June 2026, is still in limited preview rather than wide release. Gemini 3.5 Flash shipped at I/O.

Does Google make its own AI chips?

Yes. Google designs its own Tensor Processing Units (TPUs); the seventh-generation Ironwood is built for inference and an eighth generation is previewed. Owning its chips is a major cost and supply advantage, and Google now sells TPU compute to rivals — including a multibillion-dollar deal with Anthropic.

How many people use Gemini?

The Gemini app passed 900 million monthly active users by May 2026. Separately, AI Overviews in Google Search reach around 2 billion monthly users, and AI Mode reached tens of millions of daily users.

Why did Google invest in Anthropic?

In April 2026 Google committed up to $40 billion to Anthropic in cash and compute, locking in about 5 gigawatts of TPU capacity. It spreads Google’s AI bets and fills its data centres, even though Anthropic competes with Gemini — Google profits whether its own models or Anthropic’s win.

Is Gemini better than ChatGPT or Claude?

It depends on the task. Gemini leads on very large context windows and multimodal breadth and is deeply integrated into Google’s products, while Claude leads the hardest coding benchmarks and ChatGPT has the largest consumer reach. See the best AI models ranking for the current standings.

Models

Apps

• Gemini