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Editorial illustration for Nvidia and Meta ink deal; Nvidia touts hardware for inference and AI training

Nvidia-Meta Deal Fuels Next-Gen AI Hardware Revolution

Nvidia and Meta ink deal; Nvidia touts hardware for inference and AI training

2 min read

Meta’s latest partnership with Nvidia marks a rare public alignment between a social‑media heavyweight and the chipmaker that powers most of today’s large‑scale models. The agreement, announced this week, pairs Meta’s generative‑AI ambitions with Nvidia’s latest GPUs, a move that could shift how the two firms allocate compute resources across their product lines. While the details of the contract remain under wraps, analysts note that the deal underscores a broader industry trend: companies are looking beyond raw training horsepower and are increasingly focused on the day‑to‑day inference workloads that deliver user‑facing features.

For Nvidia, the partnership is an opportunity to showcase the versatility of its silicon, which it has long claimed can handle both the heavy‑lifting of frontier AI research and the lighter, real‑time demands of inference. The company declined to comment on the specifics, but its historical messaging suggests the collaboration is more than a headline. As Jensen Huang told WIRED two years ago, the firm’s hardware was built with a dual purpose in mind—something that now feels especially relevant.

Nvidia, which also declined to comment on the new deal, has for years now said that its hardware can be used for inference computing needs in addition to frontier AI training. Two years ago, in a sit-down interview with WIRED, Nvidia founder and chief executive Jensen Huang estimated that Nvidia's business was likely "40 percent inference, 60 percent training." In December, Nvidia announced it was spending $20 billion to license technology from the chip startup Groq and bring some of Groq's top talent, including CEO Jonathan Ross, into the fold at Nvidia. According to a statement from Groq, the deal reflected a "shared focus on expanding access to high-performance, low cost inference." The deal represented Nvidia's largest acquisition deal to date. Competition Heats Up Nvidia's deal with Meta comes as the most prominent AI labs and multi-trillion dollar software companies are looking to diversify their sources of compute power.

The agreement with Meta marks another step for Nvidia beyond its traditional GPU stronghold. By targeting customers who need inference rather than the most demanding training workloads, the chipmaker appears to be widening its market reach. Nvidia declined to comment on the specifics of the deal, leaving the exact terms and pricing opaque.

Its long‑standing claim that its hardware serves both inference and frontier AI training remains untested in this new context. Jensen Huang’s estimate, made two years ago, suggested that a sizable portion of Nvidia’s revenue could eventually come from such lower‑intensity use cases, but the article offers no data to confirm whether that projection is materialising. Consequently, while the partnership signals intent, it is unclear how much it will shift Nvidia’s customer base or affect overall demand for its premium GPUs.

The move underscores a strategic pivot, yet the practical impact on Nvidia’s earnings and on Meta’s AI infrastructure remains uncertain.

Further Reading

Common Questions Answered

Why did the $100 billion Nvidia and OpenAI infrastructure deal stall?

According to [cnbc.com](https://www.cnbc.com/2026/02/03/nvidia-openai-stalled-on-their-mega-deal-ai-giants-need-each-other.html), Nvidia has expressed doubts about OpenAI's business model, and the negotiations have effectively been 'on ice'. Despite the initial high-profile announcement in September, no contract has been signed, and no money has changed hands between the two companies.

How is OpenAI responding to the deteriorating relationship with Nvidia?

[iajournal.net](https://www.iajournal.net/openai-partners-with-cerebras-for-lightning-fast-code-generation-as-nvidia-relationship-deteriorates/) reports that OpenAI has partnered with Cerebras Systems to develop a new GPT-5.3-Codex-Spark model that runs on Cerebras's wafer-scale processors. This strategic move allows OpenAI to explore alternative chip architectures while maintaining that GPUs remain foundational to their core infrastructure.

What alternative computing deal has OpenAI recently signed?

[Reuters](https://reut.rs/45cAS0w) revealed that OpenAI signed a $10 billion computing deal with Cerebras, purchasing up to 750 megawatts of computing power over three years. The agreement focuses on cloud services for inference and reasoning models, with Cerebras building or leasing data centers to support OpenAI's AI products.