NVIDIA

NVIDIA Vera CPU

Name: NVIDIA Vera CPU
Brand: NVIDIA

NVIDIA Vera CPU for AI factories and HPC workloads with high single-threaded performance and massive memory bandwidth.

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Evidence statusSpecs not independently verifiednvidia.com

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Host CPU: NVIDIA Vera delivers system-level efficiency as the host CPU for AI factories, including NVIDIA Vera Rubin NVL72 and HGX™ Vera Rubin NVL8 platforms. Vera feeds GPUs for large-scale AI while running the CPU work that keeps the factory operating, including ETL, key-value (KV) cache management, and orchestration. With high single-threaded performance, massive memory bandwidth, and a single compute die design that avoids cross-chiplet latency, Vera delivers predictable performance while keeping GPUs fully utilized across accelerated AI and HPC systems.
Standalone CPU: For agentic AI, reinforcement learning, data processing, and analytics, NVIDIA Vera delivers leading per-core performance and massive memory bandwidth to run thousands of parallel sandbox environments, tool calls, code executions, evaluation loops, and data workflows. Faster CPU execution means agents wait less, RL systems generate more feedback per training step, and AI factories produce more tokens per dollar. As a standalone CPU platform, Vera also supports hyperscale cloud, enterprise, and HPC workloads and extends to storage infrastructure with NVIDIA Vera BlueField™-4 STX. Available as a dense, liquid-cooled NVIDIA Vera CPU rack or in standard dual- and single-socket configurations, Vera fits any data center.
NVIDIA NVLink-C2C: 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.
LPDDR5X Memory Subsystem: NVIDIA Vera delivers up to 1.2 terabytes per second (TB/s) of LPDDR5X memory bandwidth, providing 2x the bandwidth at half the power of traditional CPU 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.

The decision

Where it wins

High single-threaded performance for fast software execution.
Massive LPDDR5X memory bandwidth (up to 1.2 TB/s) for efficient data-intensive workloads.
Second-generation NVIDIA SCF for fast, consistent data access across cores.

Where it doesn't

Specialized design may limit applicability for general-purpose computing tasks.

Ideal forAI factories and analyticsHPC workloadsData-intensive agentic workflows

Key Features

✦Up to 1.2 TB/s LPDDR5X memory bandwidth
✦1.8 TB/s NVLink-C2C coherent bandwidth
✦Second-generation NVIDIA SCF for unified cache architecture
✦Single-threaded performance for fast software execution
✦Predictable latency and throughput for agentic workloads

02 / Technical record

Specifications

Structured product data, grouped by system.

Core hardware02

Host CPU	NVIDIA Vera delivers system-level efficiency as the host CPU for AI factories, including NVIDIA Vera Rubin NVL72 and HGX™ Vera Rubin NVL8 platforms. Vera feeds GPUs for large-scale AI while running the CPU work that keeps the factory operating, including ETL, key-value (KV) cache management, and orchestration. With high single-threaded performance, massive memory bandwidth, and a single compute die design that avoids cross-chiplet latency, Vera delivers predictable performance while keeping GPUs fully utilized across accelerated AI and HPC systems.
Standalone CPU	For agentic AI, reinforcement learning, data processing, and analytics, NVIDIA Vera delivers leading per-core performance and massive memory bandwidth to run thousands of parallel sandbox environments, tool calls, code executions, evaluation loops, and data workflows. Faster CPU execution means agents wait less, RL systems generate more feedback per training step, and AI factories produce more tokens per dollar. As a standalone CPU platform, Vera also supports hyperscale cloud, enterprise, and HPC workloads and extends to storage infrastructure with NVIDIA Vera BlueField™-4 STX. Available as a dense, liquid-cooled NVIDIA Vera CPU rack or in standard dual- and single-socket configurations, Vera fits any data center.

Host CPU

NVIDIA Vera delivers system-level efficiency as the host CPU for AI factories, including NVIDIA Vera Rubin NVL72 and HGX™ Vera Rubin NVL8 platforms. Vera feeds GPUs for large-scale AI while running the CPU work that keeps the factory operating, including ETL, key-value (KV) cache management, and orchestration. With high single-threaded performance, massive memory bandwidth, and a single compute die design that avoids cross-chiplet latency, Vera delivers predictable performance while keeping GPUs fully utilized across accelerated AI and HPC systems.

Standalone CPU

For agentic AI, reinforcement learning, data processing, and analytics, NVIDIA Vera delivers leading per-core performance and massive memory bandwidth to run thousands of parallel sandbox environments, tool calls, code executions, evaluation loops, and data workflows. Faster CPU execution means agents wait less, RL systems generate more feedback per training step, and AI factories produce more tokens per dollar. As a standalone CPU platform, Vera also supports hyperscale cloud, enterprise, and HPC workloads and extends to storage infrastructure with NVIDIA Vera BlueField™-4 STX. Available as a dense, liquid-cooled NVIDIA Vera CPU rack or in standard dual- and single-socket configurations, Vera fits any data center.

Memory & compute01

LPDDR5X Memory Subsystem	NVIDIA Vera delivers up to 1.2 terabytes per second (TB/s) of LPDDR5X memory bandwidth, providing 2x the bandwidth at half the power of traditional CPU 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.

LPDDR5X Memory Subsystem

NVIDIA Vera delivers up to 1.2 terabytes per second (TB/s) of LPDDR5X memory bandwidth, providing 2x the bandwidth at half the power of traditional CPU 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.

AI & acceleration01

NVIDIA NVLink-C2C	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.

NVIDIA NVLink-C2C

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.

Other specifications02

Single-Threaded Performance	helps software environments, tool calls, and evaluation loops complete faster, while NVIDIA Spatial Multithreading creates 176 threads with partitioned core resources for predictable throughput at scale.
Second-Generation NVIDIA SCF	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.

Single-Threaded Performance

helps software environments, tool calls, and evaluation loops complete faster, while NVIDIA Spatial Multithreading creates 176 threads with partitioned core resources for predictable throughput at scale.

Second-Generation NVIDIA SCF

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.

Evidence / qualification

Read the record

Specs not independently verifiednvidia.com

Source on record: nvidia.com

Editorial context

The NVIDIA Vera CPU is designed for high-performance computing and artificial intelligence workloads, offering exceptional single-threaded performance and massive memory bandwidth. It is ideal for AI factories, analytics, and HPC systems where predictable performance and efficient data management are critical. The Vera CPU's single compute die design minimizes cross-chiplet latency, ensuring consistent and reliable performance. However, its specialized focus and high performance requirements may limit its applicability for general-purpose computing tasks.

Frequently Asked Questions

Who is NVIDIA Vera CPU for?↓

NVIDIA Vera CPU is a fit for aI factories and analytics, HPC workloads and Data-intensive agentic workflows.

What are the drawbacks of NVIDIA Vera CPU?↓

The trade-offs we record are: Specialized design may limit applicability for general-purpose computing tasks..

What does NVIDIA Vera CPU do well?↓

High single-threaded performance for fast software execution., Massive LPDDR5X memory bandwidth (up to 1.2 TB/s) for efficient data-intensive workloads. and Second-generation NVIDIA SCF for fast, consistent data access across cores..

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