Meta announced a sweeping multi-year partnership with Nvidia on February 17 to deploy millions of processors across every layer of Nvidia's product stack in a deal analysts estimate reaches tens of billions of dollars, making Meta the first major hyperscaler to adopt Nvidia's Grace CPUs as standalone processors and signaling the company is doubling down on its AI infrastructure bet rather than diversifying to alternatives like AMD or Google TPUs.
The expanded agreement covers Nvidia's current Blackwell GPUs, forthcoming Rubin chips expected in late 2026, Grace CPUs for general computing workloads, upcoming Vera CPUs featuring 88 custom Arm cores, Spectrum-X Ethernet networking switches, and Confidential Computing security systems for WhatsApp's AI-powered private messaging features. Neither company disclosed financial terms, but chip analyst Ben Bajarin of Creative Strategies stated flatly that "the deal is certainly in the tens of billions of dollars."
Strategic Shift Toward Inference and Agentic AI
The decision to deploy Grace CPUs as standalone processors rather than exclusively paired with GPUs reflects a fundamental shift in AI workload patterns as the industry moves from training-heavy to inference-heavy operations. Meta becomes the first hyperscaler to make this architectural commitment at scale, effectively standardizing its entire AI infrastructure around Nvidia's ecosystem from compute to networking to security.
"The question of why Meta is deploying Nvidia's CPUs at scale is the most interesting thing in this announcement," Bajarin told the Financial Times. The move signals growing demand for processors optimized for agentic AI workflows where autonomous agents require different compute profiles than traditional model training.
Nvidia CEO Jensen Huang emphasized the technical integration depth: "No one deploys AI at Meta's scale—integrating frontier research with industrial-scale infrastructure to power the world's largest personalization and recommendation systems for billions of users. Through deep codesign across CPUs, GPUs, networking, and software, we are bringing the full Nvidia platform to Meta's researchers and engineers."
Timing Provides Market Reassurance Amid Volatility
The announcement arrives as AI-related stocks face significant pressure in early 2026 amid persistent concerns about unsustainable capital expenditure levels. Meta's stock has fallen 3.3% year-to-date while Microsoft has declined more than 17% since January 1. Chip stocks have also cooled as investors question whether high-powered GPUs remain necessary for all AI applications or if more specialized chips will eventually dominate.
Meta and Nvidia shares both climbed during Tuesday's trading following the announcement, while AMD stock dropped approximately 4% as the deal appeared to foreclose diversification opportunities that Meta had previously explored. In November 2025, Nvidia stock fell 4% on reports that Meta was considering Google's tensor processing units for its 2027 data center buildout, making this announcement a clear signal that Meta has recommitted to Nvidia as its primary silicon partner.
Fits Within Broader $135 Billion Infrastructure Push
The Nvidia partnership aligns with Meta CEO Mark Zuckerberg's January announcement that the company plans to spend up to $135 billion on AI infrastructure throughout 2026, one of the largest single-year technology capital expenditure commitments in corporate history. Zuckerberg described the goal as delivering "personal superintelligence to everyone in the world," his often-stated vision that AI will surpass human performance in most cognitive tasks.
Meta has been developing its own AI chips and maintains relationships with AMD, which won a notable deal with OpenAI in October as AI companies seek alternatives to Nvidia amid constrained supply. The company is also reportedly developing a new frontier model codenamed Avocado as successor to its Llama AI technology, though the most recent Llama version released in spring 2025 failed to excite developers according to CNBC reporting.
The comprehensive nature of Meta's commitment—spanning GPUs, CPUs, networking, and security across current and next-generation products—suggests the company has determined that ecosystem integration and guaranteed supply access outweigh the benefits of maintaining multiple silicon vendors. For Nvidia, securing one of its largest customers through 2027 and beyond provides revenue visibility as the company navigates increasing competition from custom AI chips developed by hyperscalers themselves.
Engineering teams from both companies will collaborate on "deep codesign to optimize and accelerate state-of-the-art AI models" for Meta's specific workloads, indicating the partnership extends beyond simple procurement into joint development efforts.
