# Vera CPU

Published articles for Vera CPU.

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## Delivering Vera: NVIDIA's First CPU Built for Agents Is Shipping Now

DevFeed: [Delivering Vera: NVIDIA's First CPU Built for Agents Is Shipping Now](<https://devfeed.tech/articles/delivering-vera-nvidia-s-first-cpu-built-for-agents-is-shipping-now-6962.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/vera-cpu-delivery/>)

Author: Ian Finder

Published: 2026-08-27T13:00:17Z

Content type: article

Language: en

Sources: [NVIDIA Blog](<https://devfeed.tech/sources/nvidia-blog.md>)

Topics: [Vera CPU](<https://devfeed.tech/topics/vera-cpu.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [NVIDIA Vera](<https://devfeed.tech/topics/nvidia-vera.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Amazon EC2](<https://devfeed.tech/topics/amazon-ec2.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [ai-training](<https://devfeed.tech/tags/ai-training.md>), [amazon-ec2](<https://devfeed.tech/tags/amazon-ec2.md>), [aws](<https://devfeed.tech/tags/aws.md>), [corporate](<https://devfeed.tech/tags/corporate.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [orchestration](<https://devfeed.tech/tags/orchestration.md>), [rubin-gpu](<https://devfeed.tech/tags/rubin-gpu.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>)

### AI overview

NVIDIA is shipping Vera, a CPU designed for agentic AI workloads, to AWS and other organizations across the AI ecosystem. The article describes Vera's 88 custom Olympus cores, 1.2TB/s memory bandwidth, and up to 1.8x faster per-core performance on agentic AI workloads, alongside its role in supporting concurrent CPU-intensive tasks such as tool calls, orchestration, retrieval, software testing, and data analysis.

### Source excerpt

NVIDIA Vice President of Hyperscale and HPC Ian Buck hand-delivers Vera CPU systems across the AI ecosystem as Vera begins shipping at scale.

## With Groq 3 LPX in Full Production, NVIDIA Extends Vera Rubin Inference for Agents

DevFeed: [With Groq 3 LPX in Full Production, NVIDIA Extends Vera Rubin Inference for Agents](<https://devfeed.tech/articles/with-groq-3-lpx-in-full-production-nvidia-extends-vera-rubin-inference-for-agents-6963.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/vera-rubin-lpx-spectrum-x-nvlink-fusion/>)

Author: NVIDIA Writers

Published: 2026-08-24T15:00:41Z

Content type: news

Language: en

Sources: [NVIDIA Blog](<https://devfeed.tech/sources/nvidia-blog.md>)

Topics: [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Low-Latency Inference](<https://devfeed.tech/topics/low-latency-inference.md>), [networking](<https://devfeed.tech/topics/networking.md>), [gemma4](<https://devfeed.tech/topics/gemma4.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [bluefi](<https://devfeed.tech/tags/bluefi.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cpx](<https://devfeed.tech/tags/cpx.md>), [groq](<https://devfeed.tech/tags/groq.md>), [groq-3-lpx](<https://devfeed.tech/tags/groq-3-lpx.md>), [inference](<https://devfeed.tech/tags/inference.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [long-context](<https://devfeed.tech/tags/long-context.md>), [low-latency-inference](<https://devfeed.tech/tags/low-latency-inference.md>), [lpx](<https://devfeed.tech/tags/lpx.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-spectrum-x-ethernet](<https://devfeed.tech/tags/nvidia-spectrum-x-ethernet.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

NVIDIA announces Groq 3 LPX production availability alongside Vera Rubin NVL72, positioning the integrated compute, networking, and inference stack for long-context, agentic AI workloads. The article highlights a benchmark result of 3,400 output tokens per second on Gemma 4 31B and describes partner adoption of Vera Rubin, Spectrum-X Multiplane, and Groq 3 LPX.

### Source excerpt

The next era of AI inference won't be defined by a single breakthrough chip, network or system. It'll be defined by how every layer of the AI factory works together. That's why NVIDIA is extending Vera Rubin NVL72 with fast token generation for agentic systems. Announced today, the NVIDIA Vera Rubin rack-scale system NVIDIA Groq [...]

## NVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories

DevFeed: [NVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories](<https://devfeed.tech/articles/nvidia-bluefield-4-powers-new-scale-in-network-infrastructure-for-agentic-ai-factories-6889.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-bluefield-4-powers-new-scale-in-network-infrastructure-for-agentic-ai-factories/>)

Author: Michelle Horton

Published: 2026-08-24T15:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [datacenter](<https://devfeed.tech/topics/datacenter.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [InfiniBand](<https://devfeed.tech/topics/infiniband.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [bluefield-dpu](<https://devfeed.tech/tags/bluefield-dpu.md>), [connectx](<https://devfeed.tech/tags/connectx.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [data-centers](<https://devfeed.tech/tags/data-centers.md>), [dsx](<https://devfeed.tech/tags/dsx.md>), [grace-cpu](<https://devfeed.tech/tags/grace-cpu.md>), [infiniband](<https://devfeed.tech/tags/infiniband.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [network](<https://devfeed.tech/tags/network.md>), [networking](<https://devfeed.tech/tags/networking.md>), [networking-communications](<https://devfeed.tech/tags/networking-communications.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

NVIDIA describes Scale-In network infrastructure for agentic AI factories, centered on BlueField-4, DOCA, and Spectrum-X Ethernet. The architecture is intended to accelerate networking, storage, security, data movement, tenant isolation, and infrastructure operations as AI compute scales.

### Source excerpt

Traditional cloud infrastructure was designed for predictable, general-purpose workloads and standard interfaces. Agentic AI factories connect diverse users,...

## Solving Agentic AI Fleet Challenges with NVIDIA Vera CPU

DevFeed: [Solving Agentic AI Fleet Challenges with NVIDIA Vera CPU](<https://devfeed.tech/articles/solving-agentic-ai-fleet-challenges-with-nvidia-vera-cpu-6941.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/solving-agentic-ai-fleet-challenges-with-nvidia-vera-cpu/>)

Author: Michelle Horton

Published: 2026-08-24T15:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [AI Bots](<https://devfeed.tech/topics/ai-bots.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [concurrency](<https://devfeed.tech/tags/concurrency.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [latency](<https://devfeed.tech/tags/latency.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [orchestration](<https://devfeed.tech/tags/orchestration.md>), [performance](<https://devfeed.tech/tags/performance.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [systems](<https://devfeed.tech/tags/systems.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

The article argues that AI-agent CPU fleets should use a balanced design that combines strong per-core performance for latency-bound sequential work with enough concurrency for intermittent parallel bursts. It presents NVIDIA Vera CPU as designed for those agentic workload patterns.

### Source excerpt

AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks....

## NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage

DevFeed: [NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage](<https://devfeed.tech/articles/nvidia-vera-storage-benchmarks-faster-encryption-compression-integrity-checking-and-recovery-for-ai-native-storage-6914.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-vera-storage-benchmarks-faster-encryption-compression-integrity-checking-and-recovery-for-ai-native-storage/>)

Author: Elizabeth Goodman

Published: 2026-08-03T16:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Encryption](<https://devfeed.tech/topics/encryption.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [Security](<https://devfeed.tech/topics/security.md>), [Resilience](<https://devfeed.tech/topics/resilience.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [bluefield-dpu](<https://devfeed.tech/tags/bluefield-dpu.md>), [cloud-apis](<https://devfeed.tech/tags/cloud-apis.md>), [cloud-networking](<https://devfeed.tech/tags/cloud-networking.md>), [cloud-services](<https://devfeed.tech/tags/cloud-services.md>), [compression](<https://devfeed.tech/tags/compression.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [doca](<https://devfeed.tech/tags/doca.md>), [encryption](<https://devfeed.tech/tags/encryption.md>), [featured](<https://devfeed.tech/tags/featured.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [networking-communications](<https://devfeed.tech/tags/networking-communications.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [security](<https://devfeed.tech/tags/security.md>), [software-defined-data-center](<https://devfeed.tech/tags/software-defined-data-center.md>), [storage](<https://devfeed.tech/tags/storage.md>), [systems](<https://devfeed.tech/tags/systems.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

NVIDIA presents benchmark results for the Vera BlueField-4 STX Storage Processor in AI-native storage workloads. The results describe faster encryption and decryption, recovery, integrity checking, compression and decompression, and multi-stage storage processing than an x86 CPU, with lower CPU and power overhead.

### Source excerpt

Storage is an active part of every agentic AI workflow. As agents retrieve enterprise knowledge, access persistent memory, reuse key-value (KV) cache data,...

## NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI

DevFeed: [NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI](<https://devfeed.tech/articles/nvidia-vera-cpu-olympus-cores-built-for-maximum-single-thread-performance-in-agentic-ai-6865.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/inside-nvidia-vera-cpu-olympus-cores-built-for-maximum-single-threaded-performance-in-agentic-ai/>)

Author: Praveen Menon

Published: 2026-07-21T18:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [cpu](<https://devfeed.tech/topics/cpu.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [code](<https://devfeed.tech/tags/code.md>), [concurrency](<https://devfeed.tech/tags/concurrency.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-analytics](<https://devfeed.tech/tags/data-analytics.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [featured](<https://devfeed.tech/tags/featured.md>), [latency](<https://devfeed.tech/tags/latency.md>), [memory](<https://devfeed.tech/tags/memory.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [sandboxes](<https://devfeed.tech/tags/sandboxes.md>), [tools](<https://devfeed.tech/tags/tools.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

The article explains how NVIDIA's Vera CPU and its Olympus cores are designed for the single-threaded performance, memory bandwidth, and predictable latency required by concurrent agentic AI workloads.

### Source excerpt

Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with...

## Scaling Agentic AI Factories Through Extreme Co-Design with NVIDIA BlueField

DevFeed: [Scaling Agentic AI Factories Through Extreme Co-Design with NVIDIA BlueField](<https://devfeed.tech/articles/scaling-agentic-ai-factories-through-extreme-co-design-with-nvidia-bluefield-6937.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/scaling-agentic-ai-factories-through-extreme-co-design-with-nvidia-bluefield/>)

Author: Michelle Horton

Published: 2026-07-16T16:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Network](<https://devfeed.tech/topics/network.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Security](<https://devfeed.tech/topics/security.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [systems](<https://devfeed.tech/topics/systems.md>), [NVIDIA Research](<https://devfeed.tech/topics/nvidia-research.md>)

Tags: [accelerate](<https://devfeed.tech/tags/accelerate.md>), [agent](<https://devfeed.tech/tags/agent.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [compute](<https://devfeed.tech/tags/compute.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [dsx](<https://devfeed.tech/tags/dsx.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [memory](<https://devfeed.tech/tags/memory.md>), [network](<https://devfeed.tech/tags/network.md>), [networking](<https://devfeed.tech/tags/networking.md>), [networking-communications](<https://devfeed.tech/tags/networking-communications.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [policy](<https://devfeed.tech/tags/policy.md>), [storage](<https://devfeed.tech/tags/storage.md>), [tool](<https://devfeed.tech/tags/tool.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

This article explains how agentic AI and long-context inference create demanding data-path requirements for AI factories. It describes NVIDIA BlueField-4, Vera BlueField-4 STX, and DOCA as infrastructure technologies that offload, accelerate, and isolate networking, storage, security, telemetry, and control-plane services while improving utilization, latency, isolation, cost per token, and energy efficiency.

### Source excerpt

Agentic AI changes the infrastructure pattern for AI factories. One request can trigger many model calls, tool calls, memory lookups, policy checks, storage...

## NVIDIA Vera CPU Boosts AI Factory Throughput to Accelerate Agentic Workloads

DevFeed: [NVIDIA Vera CPU Boosts AI Factory Throughput to Accelerate Agentic Workloads](<https://devfeed.tech/articles/nvidia-vera-cpu-boosts-ai-factory-throughput-to-accelerate-agentic-workloads-6910.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-vera-cpu-boosts-ai-factory-throughput-to-accelerate-agentic-workloads/>)

Author: Michelle Horton

Published: 2026-07-07T18:10:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Vera CPU](<https://devfeed.tech/topics/vera-cpu.md>), [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Orchestration](<https://devfeed.tech/topics/orchestration.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Cache](<https://devfeed.tech/topics/cache.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>), [Neural Network](<https://devfeed.tech/topics/neural-network.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [cache](<https://devfeed.tech/tags/cache.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [featured](<https://devfeed.tech/tags/featured.md>), [inference](<https://devfeed.tech/tags/inference.md>), [model](<https://devfeed.tech/tags/model.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [orchestration](<https://devfeed.tech/tags/orchestration.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rl](<https://devfeed.tech/tags/rl.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>)

### AI overview

This NVIDIA developer article explains how the NVIDIA Vera CPU can improve AI factory throughput for agentic workloads. It emphasizes sustained per-core performance for CPU tasks between model steps, including tool calls, code execution, sandbox evaluations, data processing, orchestration, KV-cache coordination, and result handling. The article also describes how CPU performance affects reinforcement learning rollouts, user response time, and cached-context efficiency.

### Source excerpt

Agentic systems turn model reasoning into action through multi-step workflows that combine inference, tool use, code execution, retrieval, orchestration, and...