NVIDIA Vera CPU Launched for Agentic AI Workloads
NVIDIA has introduced the Vera CPU, a processor built specifically for agentic AI and reinforcement learning workloads. According to NVIDIA, it delivers results with 50% faster performance and twice the efficiency compared to traditional rack-scale CPUs.
Technical Specifications
The Vera CPU features 88 custom NVIDIA-designed Olympus cores, each capable of running two tasks using NVIDIA Spatial Multithreading. It includes a high-bandwidth memory subsystem built on LPDDR5X memory and uses the second-generation NVIDIA Scalable Coherency Fabric for faster agentic responses under high utilization conditions.
System Configurations
- New Vera CPU rack integrates 256 liquid-cooled Vera CPUs
- Sustains more than 22,500 concurrent CPU environments running independently at full performance
- Built using NVIDIA MGX modular reference architecture
- Part of NVIDIA Vera Rubin NVL72 platform with NVIDIA GPUs connected via NVIDIA NVLink-C2C interconnect
- Provides 1.8 TB/s of coherent bandwidth (7x PCIe Gen 6 bandwidth)
- Also serves as host CPU for NVIDIA HGX Rubin NVL8 systems
- Systems integrate NVIDIA ConnectX SuperNIC cards and NVIDIA BlueField-4 DPUs
Adoption and Partners
Customers collaborating with NVIDIA to deploy Vera CPU include Alibaba, ByteDance, Meta, Oracle Cloud Infrastructure, CoreWeave, Lambda, Nebius, and Nscale. Manufacturing partners include Dell Technologies, HPE, Lenovo, Supermicro, ASUS, Compal, Foxconn, GIGABYTE, Pegatron, Quanta Cloud Technology (QCT), Wistron, and Wiwynn.
Target Workloads
Vera systems are designed for reinforcement learning, agentic inference, data processing, orchestration, storage management, cloud applications, and high-performance computing. Systems partners provide both dual and single-socket CPU server configurations.
According to Jensen Huang, NVIDIA's CEO, "The CPU is no longer simply supporting the model; it's driving it. With breakthrough performance and energy efficiency, Vera unlocks AI systems that think faster and scale further."
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