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NVIDIA and Meta announced a multiyear partnership on February 17, 2026, covering AI data-center compute, networking, cloud infrastructure and model development. NVIDIA says the plan will enable large-scale deployment of its CPUs and millions of Blackwell and Rubin GPUs, but the companies have not disclosed a precise GPU count, deal value or complete delivery schedule. The announcement describes intended scope—not confirmation that all equipment is already delivered or deployed.
What did NVIDIA and Meta announce?
The companies described the agreement as a multiyear, multigenerational strategic partnership supporting Meta’s long-term AI infrastructure roadmap. It builds on an existing relationship and spans Meta’s on-premises data centers, cloud deployments and AI infrastructure. Meta says it plans to build hyperscale data centers for both AI training and inference, serving its long-term roadmap and core business. Meta’s announcement and NVIDIA’s announcement set out the companies’ plans; neither establishes that every announced system has been delivered.
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What hardware and infrastructure are included?
| Component | Role and announced status | Timeline or certainty |
|---|---|---|
| Blackwell and Rubin GPUs | NVIDIA says the partnership will enable deployment of millions of its GPUs for Meta’s AI infrastructure. The release gives no total count or model-by-model quantities. | Partnership scope announced; no complete shipment or deployment calendar disclosed. |
| Grace CPUs | NVIDIA says the companies are continuing work on Arm-based Grace CPUs for Meta data-center production applications. NVIDIA calls this a first large-scale Grace-only deployment. | No specific delivery schedule stated in the announcement. |
| Vera CPUs and Vera Rubin platform | The companies are collaborating on Vera CPUs. Meta’s Mark Zuckerberg said they were excited to build clusters using Vera Rubin. | NVIDIA describes a large-scale Vera CPU deployment in 2027 as a possibility, not a guaranteed deadline for Vera or Vera Rubin systems. |
| GB300-based systems | NVIDIA says Meta will deploy GB300-based systems as part of its AI infrastructure. | The announcement does not provide a full delivery schedule. |
| Spectrum-X Ethernet | Meta says it adopted Spectrum-X across its infrastructure footprint for AI-scale networking. NVIDIA specifies integration of Spectrum-X switches with Meta’s Facebook Open Switching System platform. | Adoption is stated by Meta; the announcement does not give a separate rollout calendar. |
| Cloud and on-premises architecture | NVIDIA says Meta will create a unified architecture spanning on-premises data centers and NVIDIA Cloud Partner deployments. | No specific cloud-partner deployment dates or locations stated. |
What will Meta use the systems for?
AI training and inference
Meta says its hyperscale data centers will be optimized for both training AI models and running inference—the computation used to generate results from trained models. The announcement frames this work as infrastructure for Meta’s long-term AI roadmap and core business; it does not specify which individual models will run on which hardware.
Production workloads and CPU design
Grace CPUs are intended for data-center production applications. NVIDIA attributes improved performance per watt to the combination of deployment and software/library co-design. That is NVIDIA’s claim in the announcement, not an independently measured benchmark published with it.
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The companies are also working together on Vera CPUs. NVIDIA says a large-scale deployment in 2027 is possible. Zuckerberg’s reference to building Vera Rubin clusters expresses the companies’ stated direction, not a firm delivery date for all Vera or Vera Rubin systems.
Networking and unified operations
Meta says it adopted Spectrum-X Ethernet across its infrastructure footprint, while NVIDIA describes integrating switches with Meta’s Facebook Open Switching System platform. The companies say the networking approach is intended to provide predictable, low-latency performance, utilization, and operational and power efficiency. These are stated benefits, not independently verified results in the announcements.
NVIDIA also describes a unified architecture joining Meta’s on-premises data centers with NVIDIA Cloud Partner deployments. The announcements do not identify specific cloud partners, sites or rollout dates.
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Model development and WhatsApp private processing
The companies say their engineering teams are co-designing and optimizing AI models across Meta’s core workloads. Meta also says it adopted NVIDIA Confidential Computing for WhatsApp private processing, with the aim of enabling AI-powered capabilities while protecting the confidentiality and integrity of user data. The companies say they are exploring additional Meta use cases. The announcement does not independently audit or prove a privacy outcome.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is confirmed—and what remains undisclosed?
- Announced scale: NVIDIA says the plan enables millions of Blackwell and Rubin GPUs, but provides no precise count or model-by-model breakdown.
- Potential Vera timing: 2027 is the only specific future year given for a possible large-scale Vera CPU deployment; it is not a committed delivery deadline.
- Financial terms: Neither announcement provides a deal value or purchase price. The multiyear partnership should not be read as a disclosed one-time purchase amount.
- Delivery and results: The announcements do not provide a confirmed delivered-unit count, a complete deployment calendar or independently published performance benchmarks.
The announcements are authoritative statements of the companies’ plans, not independent verification of deployment or measured benefits. NVIDIA’s release also cautions that forward-looking statements are not guarantees of future performance.
Why the partnership matters
The scope goes beyond a GPU order: it combines GPUs, CPUs, networking, cloud and on-premises operations, model co-design and a privacy-focused WhatsApp use case. For Meta, the stated objective is infrastructure for both AI training and inference. For NVIDIA, the deal extends its platform across more parts of a major customer’s data-center stack. The scale and outcomes will be clearer only as the companies disclose deployments and results; the February announcement itself does not quantify those outcomes.
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