Alphabet’s rise in artificial intelligence isn’t just about fancy models or bigger search engines anymore. In a bold new move, Google is pushing hard into AI hardware with its custom TPUs (tensor processing units), now offering them directly to customers like Meta. This comes on the heels of the Gemini 3 rollout, record-smashing profits, and surging AI demand across cloud and search. Taken together, it marks a turning point: Google isn’t just participating in the AI boom. It’s aiming to lead it. The Google vs Nvidia AI chips battle is no longer theoretical—it’s happening in real time.
That leadership is showing up everywhere. Google Cloud’s AI business is booming. Gemini 3 is becoming a flagship brand. And Meta’s potential multibillion-dollar partnership for on-premise TPUs signals that customers see Google as a credible rival to Nvidia. Add four straight earnings beats, 650 million Gemini users, and growing adoption of AI-powered search, and the narrative starts to look clear: Alphabet is building an AI empire. The only question is how far it can go.
Gemini 3: From Experiment to Flagship
It wasn’t long ago that OpenAI’s ChatGPT seemed untouchable. Today, Google’s Gemini 3 is holding its own. With features like Deep Think, generative UIs, and “vibe coding” for developers, Gemini 3 is more than a chatbot. It’s an ecosystem—and it’s catching on fast. According to Alphabet’s latest earnings call, Gemini app usage has tripled since Q2, hitting over 650 million monthly active users. That kind of traction is rare, even for Google.
Gemini isn’t just user-facing either. Google is embedding it across the stack. Search now includes AI Mode, which has 75 million daily active users globally. Chrome, YouTube, and Android are also layering in Gemini tools. The result? Google is training consumers to expect generative AI in their daily workflows—and monetizing that behavior across ads, subscriptions, and devices.
Importantly, Gemini’s reach bolsters Google’s advantage in data. With over 1.3 quadrillion tokens processed per month, Alphabet has a unique data flywheel for training future models. This also supports the bullish case for advertisers: AI Overviews and AI Max in Search are expanding monetizable queries at scale. That makes Gemini 3 not just a cool feature, but a growth engine.
Google Cloud Is Quietly Eating AI
Under the radar, Google Cloud has become a $15.2 billion quarterly business with a 24% operating margin. AI is the rocket fuel. In Q3 2025, revenue from products built on Google’s own generative AI models grew more than 200% year over year. Cloud backlog hit $155 billion, up 46% quarter-over-quarter. Those numbers tell a story: Google is finally turning AI into enterprise dollars.
Here’s why that matters. While AWS and Azure still lead in market share, Google Cloud is winning on technical merit. Its full-stack approach—own chips, own models, own infra—is drawing in enterprise giants. Nine of the top 10 AI labs use Google Cloud. Gemini Enterprise already has 2 million seats across 700 companies. And customers like Banco BV and FairPrice are deploying AI at scale.
And now comes the real power play: Google vs Nvidia AI chips. By pitching TPUs directly to clients like Meta for on-prem use, Alphabet is aiming to break Nvidia’s monopoly. If it works, Google Cloud won’t just sell compute. It will shape the AI hardware layer itself. That’s a different kind of moat.
Google vs Nvidia AI Chips: The Meta Deal
The announcement that Meta may install Google TPUs starting in 2027 is a turning point. Until now, TPUs were confined to Google Cloud data centers. But by going on-prem, Google is signaling it wants to compete with Nvidia at the silicon level. And Meta’s interest shows that Big Tech wants alternatives.
According to internal Google Cloud projections, broader TPU adoption could capture up to 10% of Nvidia’s revenue—a swing worth billions. High-frequency trading firms and banks are also being pitched on the benefits of TPUs for compliance-sensitive workloads. The sales pitch is clear: Google TPUs offer more control, lower latency, and in some cases, better economics.
This shift could expand Google’s influence beyond just cloud compute. It puts them in the hardware supply chain, which is where Nvidia currently dominates. And with companies desperate for AI chips amid tight supply, a credible second source is welcome.
Still, “Google vs Nvidia AI chips” is more of a story in progress than a done deal. Nvidia has deep developer loyalty, entrenched CUDA software, and years of momentum. But Alphabet has capital, customers, and infrastructure. If TPUs gain ground, the AI chip wars could go from speculation to street fight.
Valuation and the Bear Case: It’s Not All Cheap
For all the bullishness, Alphabet’s stock isn’t exactly a value play anymore. Shares are up nearly 90% in the past 12 months and now trade at 31x trailing earnings and over 25x LTM EBIT. Valuation multiples have stretched meaningfully with the LTM EV/EBITDA at 26.1x and the LTM P/E at 31.45x. Even NTM price/sales is nearly 9x. That’s a long way from where Alphabet traded when AI fears peaked in 2024. About half the stock’s gain came from multiple expansion, not earnings growth. And while Gemini and TPUs are exciting, the costs of building and maintaining AI infrastructure are climbing fast. Depreciation rose 41% YoY last quarter, and CapEx could hit $93 billion this year.
There’s also the bear case that Gemini doesn’t fully close the gap with OpenAI, or that Meta decides to stick with Nvidia for hardware. Search disruption from agentic AI isn’t off the table, and regulatory scrutiny continues. The “Google vs Nvidia AI chips” narrative could easily run into real-world delays, adoption hurdles, or competitive responses from rivals like Amazon and AMD.ily run into real-world delays, adoption hurdles, or competitive responses from rivals like Amazon and AMD.
Final Thoughts: A New Era, But at What Price?
Alphabet is no longer just the AI sleeper among the Magnificent Seven. With the Gemini 3 rollout, surging profits, and an aggressive push into AI chips via the Meta TPU deal, it’s staking its claim as a serious AI winner.
That said, the valuation is no longer cheap. LTM EV/EBIT of 30x and free cash flow multiples above 50x suggest a lot of optimism is already priced in. For investors, the key question isn’t whether Google is winning in AI—it’s whether it’s winning enough to justify these multiples.
Still, the optionality is enormous. Google Cloud is growing fast. Gemini is gaining users. Search monetization is holding up. And TPUs could unlock a whole new revenue layer. If the execution matches the ambition, Alphabet could reshape the AI hardware narrative. But for now, the battle lines are drawn. Google vs Nvidia AI chips—it’s game on.
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