NVIDIA Vera

NVIDIA Vera features 88 custom NVIDIA Olympus cores built for complex, branch-heavy, latency-sensitive work behind agentic AI and reinforcement learning. High single-thread performance helps agent runtimes, tool calls, code execution, and evaluation loops complete faster, while NVIDIA Spatial Multithreading™ creates 176 threads with partitioned core resources for predictable throughput at scale.

NVIDIA Vera delivers up to 1.2 terabytes per second (TB/s) of LPDDR5X memory bandwidth, while using significantly lower power than traditional server memory. This keeps thousands of parallel software environments responsive while supporting faster RL iterations, efficient KV-cache management, and data-intensive agentic workflows. With up to 1.5 TB of memory, Vera provides the capacity and efficiency for AI factories, analytics, and HPC workloads.

NVIDIA Vera uses second-generation NVIDIA SCF to connect all 88 cores, cache, memory, input and output (IO), and NVLink-C2C across a single compute die. With 3.4 TB/s of bisectional bandwidth and a unified cache architecture, SCF gives cores fast, consistent access to data even when the CPU is fully utilized. By avoiding cross-chiplet communication, Vera maintains predictable latency and throughput for agentic workloads, analytics, and AI factory infrastructure at scale.

NVIDIA NVLink-C2C delivers up to 1.8 TB/s of coherent bandwidth between Vera CPUs and NVIDIA GPUs. When paired with NVIDIA Rubin GPUs, Vera creates a unified memory architecture that helps CPUs and GPUs work together on complex AI and HPC workloads, large datasets, and KV-cache offload. NVLink-C2C reduces data-transfer bottlenecks, simplifies optimization, supports secure isolation for sensitive data and code, and enables high-speed connectivity in dual-socket Vera CPU systems.