Riding The Momentum Of Gemini 3, “Google Chain” Challenges “Nvidia Chain,” Reshaping The Ai Trading Landscape

Google Is Leveraging Its Latest Breakthrough In Ai Models To Mount A Comprehensive Challenge Against Nvidia’s Chip Dominance. The Search Giant Has Begun Pitching Proposals To Major Clients Such As Meta To Deploy Tpu Chips In Their Own Data Centers, Aiming To Expand This Alternative Ai Chip From Google Cloud’s Rental Business Into A Broader Market.

According To Media Reports Citing Insiders, Meta Is Negotiating With Google To Use Tpu Chips Worth Billions Of Dollars In Its Data Centers By 2027, While Planning To Rent Chips From Google Cloud Next Year. This Potential Deal Could Allow Google To Capture Around 10% Of Nvidia’s Annual Revenue, Generating Billions In New Income, A Target Some Google Cloud Leaders Have Conveyed Internally.

Google’s Release Of The Gemini 3 Large Language Model This Month Triggered A Strong Market Reaction. Trained Primarily On Tpu Chips, Gemini 3’s Performance Has Approached Or Even Surpassed Openai’s Chatgpt, Prompting Investors To Reassess The Ai Chip Landscape. Google’s Stock Jumped 6.3% In A Single Day To A Record High Of Usd 318.58, Up 68% Year To Date, While Nvidia Fell Nearly 10% This Month, Narrowing Their Market Cap Gap To Usd 526 Billion, The Smallest Since April Last Year.

Nvidia Ceo Jensen Huang Has Responded Quickly To This Threat. After Google Struck A Deal With Anthropic To Provide Up To One Million Tpus, Huang Announced A Multi‑Billion‑Dollar Investment In The Company And Secured Its Commitment To Continue Using Nvidia Gpus. Similarly, Following Reports That Openai Planned To Rent Tpus From Google Cloud, Huang Reached A Preliminary Agreement To Invest Up To Usd 100 Billion To Help Openai Build Its Own Data Centers And Discuss Leasing Nvidia Gpus.

Google’s Tpu Strategy Upgrade: From Cloud Rental To On‑Premises Deployment - For Years, Google Has Rented Its Tensor Processing Unit (Tpu) Chips To Cloud Customers Using Them In Google Cloud Data Centers. Now It Is Proposing A New Plan To Clients Including Meta And Large Financial Institutions: Deploy Tpus In Their Own Facilities. Insiders Confirm Meta Is Negotiating Both Next Year’s Rental Of Google Cloud Chips And Tpu Deployment In Meta’s Data Centers By 2027. Meta Currently Relies Heavily On Nvidia Gpus.

A Person With Direct Knowledge Said Google Emphasizes That Clients Want On‑Premises Chips To Meet Higher Security And Compliance Requirements, Especially For Sensitive Data. Google Also Notes Tpus Could Particularly Benefit High‑Frequency Trading Firms Running Ai Models In Their Own Sites.

To Support The “Tpu@Premises” Initiative, Google Developed Software Called “Tpu Command Center” To Make These Chips Easier For Clients To Use. The Software Is Viewed As Google’s Countermeasure To One Of Nvidia’s Greatest Advantages—Cuda. Cuda Has Become The De Facto Standard For Ai Developers, Who Are Highly Familiar With Running Models On Nvidia Chips. Although Google’s Jax Language Is Less Familiar, Google Has Told Clients They Can Operate Tpus Using Software Related To Pytorch Without Needing Expertise In Jax.

Beginning Last Summer, Google More Aggressively Expanded The Tpu Market, Approaching Smaller Cloud Providers That Primarily Rent Nvidia Chips And Proposing They Host Tpus In Their Data Centers. Google Reached At Least One Agreement With London‑Based Fluidstack To Host Tpus In A New York Facility. As Part Of The Deal, Google Offered A Backstop: If Fluidstack Could Not Pay Its Upcoming New York Data Center Lease, Google Would Provide Up To Usd 3.2 Billion In Support.

Gemini 3 Breakthrough Reshapes Market Confidence - Google’s Current Momentum In Ai May Aid Its Tpu Push. The Newly Released Gemini 3 Model Earned Enthusiastic Praise From Noted Tech Figures, Who Believe Google Has Eliminated The Gap With Openai. Reports Indicate Gemini 3 Is Faster, Sharper, And Exhibits Deeper Reasoning Than Openai’s Chatgpt, Elon Musk’s Grok, And Jeff Bezos‑Backed Perplexity, With Pricing Comparable To Or Lower Than Rival Models.

Critically, Gemini 3 Was Trained Mainly On Google’s Tpus Rather Than Nvidia Chips. While Tpus Are Less Flexible Than Nvidia Gpus, They Are Cheaper To Develop And Consume Less Power At Full Load. Ben Reitzes, Technology Strategist At Melius Research, Said: “Some Investors Are Very Concerned That, Due To The Major Improvements In Gemini And The Continued Advantages Of Custom Tpu Chips, Alphabet Will Win The Ai War.”

Some Developers Believe Tpus Have Narrowed Nvidia’s Lead In Powering Dense Server Clusters Needed To Train New Large Ai Models. Insiders Say Meta Is Discussing Using Tpus To Train New Ai Models, Not Merely Supporting Inference For Existing Ones—Notable Because Many Analysts Previously Saw The Greatest Opportunity To Challenge Nvidia In Inference, With Training Remaining Firmly In Nvidia’s Grip.

D.A. Davidson Analyst Gil Luria Estimates That If Google’s Deepmind Ai Lab And Tpu Sales Were Spun Out As A Separate Unit, It Could Be Worth Nearly Usd 1 Trillion, Making It “Arguably One Of Alphabet’s Most Valuable Businesses.” Google’s 68% Rally This Year Reflects Such Expectations, Handily Outpacing The “Magnificent Seven” Index’s 22% And The Nasdaq Composite’s 18%. Broadcom, Google’s Tpu Manufacturing Partner, Has Also Risen More Than 63% This Year.

Nvidia’s Defensive Countermoves - Whether Or Not Google’s Tpu Effort Ultimately Succeeds, The Prospect Of A Strong Alternative To Nvidia Already Benefits Major Clients Such As Anthropic And Openai Seeking Supplier Diversification. After Google Agreed To Supply Anthropic Up To One Million Tpus, Huang Announced Another Multi‑Billion‑Dollar Investment And Secured Anthropic’s Commitment To Use Nvidia Gpus.

Likewise, After News Broke That Openai Planned To Rent Tpus From Google Cloud, Huang Reached A Preliminary Agreement To Invest Up To Usd 100 Billion To Help Openai Develop Its Own Data Centers And Discuss Leasing Nvidia Gpus. A Nvidia Spokesperson Said The Company’s Investments In Ai Startups Do Not Require Them To Buy Its Gpus. Huang May Also Seek A Deal With Meta To Preempt A Tpu Agreement With Google, As Meta Is One Of Nvidia’s Largest Customers.

Huang Has Acknowledged Google’s Progress In Ai Chips. In A Podcast Last Fall, He Told Investor Brad Gerstner That Given Google Has Produced Seven Generations Of Tpus, “We Must Show Respect Where Respect Is Due.” Nvidia Has Made Similar Financial Commitments To Ai Cloud Partners Such As Coreweave.

Meta’s Spokesperson Declined Comment On Tpu Talks. Google’s Spokesperson Did Not Comment On The Tpu Push But Said The Company “Is Experiencing Accelerated Demand For Both Our Custom Tpus And Nvidia Gpus; We Are Committed To Supporting Both, As We Have Done For Years.”

Market Landscape Faces Restructuring - According To Trading Desk Insights, Goldman Sachs Global Banking & Markets Trader Rich Privorotsky Recently Noted That The Gemini 3 Breakthrough Is A “Disruptive Model” Reshaping The Ai Investment Ecosystem, Delaying Competitors’ Product Cycles, Driving Up Capital Expenditures, And Making Returns More Uncertain. He Emphasized That Despite Solid Earnings, Nvidia Is No Longer The Core Focus Of Ai Investment.

Melius Research’s Ben Reitzes Warned: “It Is Too Early To Declare Alphabet The Long‑Term Ai Winner. That Said, Semiconductor And Hyperscale Cloud Companies (Especially Oracle) Must Recognize The ‘Alphabet Problem’ As A Worrying Factor.” Oracle Has Purchased Billions Of Dollars Of Nvidia Chips To Rent Via Its Cloud, And If Others Build Competing Ai Clouds, Cheaper Tpus Could Pressure Pricing.

Even A Modest Narrowing Of Nvidia’s Ai Advantage Could Set Off Market Ripples In The Coming Months. If Lower‑Cost Chips Prove Equally Capable, Companies That Have Invested Heavily In Nvidia Semiconductors Could Experience Buyer’s Remorse. Valuations Are Already Elevated, From Public Hyperscalers To Openai, And How New Technologies Will Benefit The Real Economy Remains Unclear. Indeed, According To An Internal Memo Published By The Information Last Week, Openai Ceo Sam Altman Acknowledged That Google’s Ai Advances May Create “Some Temporary Economic Headwinds” For The Company, Saying, “I Expect The Atmosphere Outside Will Be Difficult For A While.”

Bernstein Senior Analyst Stacy Rasgon Told Cnbc: “We Are Not Yet At The Point Of Worrying About Who Wins Or Loses. More Important Is Whether The Opportunity In Ai Is Sustainable. If It Is, They Will All Be Fine; If Not, They Will All Encounter Trouble.”