# NVIDIA Vera

Published articles for NVIDIA Vera.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories

DevFeed: [AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories](<https://devfeed.tech/articles/ai-infra-summit-nvidia-vera-rubin-and-dsx-platform-advancements-showcase-energy-efficiencies-of-optimizing-tokens-per-watt-for-ai-factories-26942.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/ai-infra-summit-vera-rubin-dsx-energy-efficiencies-tokens-per-watt-ai-factories/>)

Author: NVIDIA Writers

Published: 2026-09-15T16:55:40Z

Content type: news

Language: en

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

Topics: [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [DSX](<https://devfeed.tech/topics/dsx.md>), [Vera Rubin](<https://devfeed.tech/topics/vera-rubin.md>), [Low-Latency Inference](<https://devfeed.tech/topics/low-latency-inference.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [Conversational AI](<https://devfeed.tech/topics/conversational-ai.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [dsx](<https://devfeed.tech/tags/dsx.md>), [inference](<https://devfeed.tech/tags/inference.md>), [infra](<https://devfeed.tech/tags/infra.md>), [latency](<https://devfeed.tech/tags/latency.md>), [low-latency-inference](<https://devfeed.tech/tags/low-latency-inference.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-blackwell](<https://devfeed.tech/tags/nvidia-blackwell.md>), [nvidia-dsx](<https://devfeed.tech/tags/nvidia-dsx.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>)

### AI overview

NVIDIA's AI Infra Summit coverage describes collaborations and platform updates focused on improving AI factory efficiency. The article highlights Vera Rubin systems, DSX MaxLPS, Dynamo inference software, NVLink and networking technologies, including claims of up to 1.4x more tokens per megawatt through factory-wide power optimization.

### Source excerpt

Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience -- with more than 8,000 attendees this year, up from 3,500 last year -- [...]

## d-Matrix Joins the NVIDIA NVLink Fusion Platform

DevFeed: [d-Matrix Joins the NVIDIA NVLink Fusion Platform](<https://devfeed.tech/articles/d-matrix-joins-the-nvidia-nvlink-fusion-platform-14008.md>)

Original publisher: [Read original article](<https://www.servethehome.com/d-matrix-joins-the-nvidia-nvlink-fusion-platform/>)

Author: Cliff Robinson

Published: 2026-09-12T21:42:59Z

Content type: news

Language: en

Sources: [ServeTheHome](<https://devfeed.tech/sources/servethehome.md>)

Topics: [d-matrix](<https://devfeed.tech/topics/d-matrix.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [xpu](<https://devfeed.tech/topics/xpu.md>), [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [datacenter](<https://devfeed.tech/topics/datacenter.md>), [networking](<https://devfeed.tech/topics/networking.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Spectrum-X](<https://devfeed.tech/topics/spectrum-x.md>)

Tags: [accelerators](<https://devfeed.tech/tags/accelerators.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-accelerator](<https://devfeed.tech/tags/ai-accelerator.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [d-matrix](<https://devfeed.tech/tags/d-matrix.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [ethernet](<https://devfeed.tech/tags/ethernet.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [server](<https://devfeed.tech/tags/server.md>), [xpu](<https://devfeed.tech/tags/xpu.md>)

### AI overview

d-Matrix and NVIDIA announced that d-Matrix will bring its next-generation XPUs to the NVLink Fusion platform. The integration is intended to support scaling from individual Raptor XPUs to larger rack-scale and clustered deployments for AI inference, alongside NVIDIA networking and CPU technologies.

### Source excerpt

d-Matrix and NVIDIA announced that d-Matrix will use NVLink Fusion to scale up and out with its next-gen Raptor AI accelerators The post d-Matrix Joins the NVIDIA NVLink Fusion Platform appeared first on ServeTheHome.

## d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment

DevFeed: [d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment](<https://devfeed.tech/articles/d-matrix-adopts-nvidia-nvlink-fusion-for-rack-scale-xpu-deployment-6947.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/d-matrix-nvlink-fusion/>)

Author: Jesse Clayton

Published: 2026-09-10T13:00:21Z

Content type: news

Language: en

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

Topics: [NVLink](<https://devfeed.tech/topics/nvlink.md>), [AI Platform](<https://devfeed.tech/topics/ai-platform.md>), [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [ai-platform](<https://devfeed.tech/tags/ai-platform.md>), [corporate](<https://devfeed.tech/tags/corporate.md>), [d-matrix](<https://devfeed.tech/tags/d-matrix.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [latency](<https://devfeed.tech/tags/latency.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [spectrum-x](<https://devfeed.tech/tags/spectrum-x.md>), [xpu](<https://devfeed.tech/tags/xpu.md>)

### AI overview

d-Matrix announced plans to use NVIDIA NVLink Fusion to connect its next-generation Raptor XPUs with NVIDIA AI infrastructure. The article describes using NVLink, Spectrum-X networking and MGX rack designs to support rack-scale, low-latency inference deployments.

### Source excerpt

AI inference chipmaker d-Matrix today announced it will use NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA's AI infrastructure platform -- joining a growing roster of ecosystem partners. By connecting Raptor to NVIDIA NVLink scale-up and Spectrum-X scale-out networking, the NVIDIA MGX rack architecture and the broader NVIDIA AI platform, NVLink Fusion gives [...]

## ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer

DevFeed: [ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer](<https://devfeed.tech/articles/asus-lays-out-a-full-ai-factory-platform-vera-rubin-nvl72-racks-stx-storage-and-a-governance-layer-12358.md>)

Original publisher: [Read original article](<https://www.storagereview.com/news/asus-lays-out-a-full-ai-factory-platform-vera-rubin-nvl72-racks-stx-storage-and-a-governance-layer>)

Author: Lyle Smith

Published: 2026-09-04T17:54:45Z

Content type: article

Language: en

Sources: [StorageReview.com](<https://devfeed.tech/sources/storagereview-com.md>)

Topics: [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [AI Platform](<https://devfeed.tech/topics/ai-platform.md>), [NVIDIA Vera Rubin](<https://devfeed.tech/topics/nvidia-vera-rubin.md>), [NVIDIA DGX](<https://devfeed.tech/topics/nvidia-dgx.md>), [NVIDIA Vera](<https://devfeed.tech/topics/nvidia-vera.md>), [MLOps](<https://devfeed.tech/topics/mlops.md>), [NVIDIA DSX](<https://devfeed.tech/topics/nvidia-dsx.md>), [ai-governance](<https://devfeed.tech/topics/ai-governance.md>), [Server](<https://devfeed.tech/topics/server.md>)

Tags: [2026](<https://devfeed.tech/tags/2026.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-governance](<https://devfeed.tech/tags/ai-governance.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [asus](<https://devfeed.tech/tags/asus.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [mlops](<https://devfeed.tech/tags/mlops.md>), [nvidia-dsx](<https://devfeed.tech/tags/nvidia-dsx.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [object-storage](<https://devfeed.tech/tags/object-storage.md>), [platform](<https://devfeed.tech/tags/platform.md>), [storage](<https://devfeed.tech/tags/storage.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

ASUS is broadening its AI infrastructure business from individual servers to a full AI factory platform covering accelerated computing, networking, storage, deployment, infrastructure management, MLOps, and governance. The article describes NVIDIA DSX-based planning, ASUS deployment and management tools, governance for AI services and autonomous agents, and server systems based on NVIDIA Vera Rubin hardware.

### Source excerpt

ASUS is expanding its role in AI infrastructure, moving from individual AI servers to platforms for building, deploying, and operating entire AI factories. At AI Tech 2026 in Seoul, the company laid out a broader strategy that brings accelerated computing, networking, storage, deployment software, infrastructure management, and AI governance together under one platform. That puts The post ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer appeared first on StorageReview.com.

## 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 [...]

## How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin

DevFeed: [How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin](<https://devfeed.tech/articles/how-nvidia-groq-3-lpx-unlocks-ultrafast-interactivity-at-long-context-on-nvidia-vera-rubin-6843.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/how-nvidia-groq-3-lpx-unlocks-ultrafast-interactivity-at-long-context-on-nvidia-vera-rubin/>)

Author: Tanya Lenz

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: [d-matrix](<https://devfeed.tech/topics/d-matrix.md>), [Vera Rubin](<https://devfeed.tech/topics/vera-rubin.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [gemma4](<https://devfeed.tech/topics/gemma4.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Cache](<https://devfeed.tech/topics/cache.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [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-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [cache](<https://devfeed.tech/tags/cache.md>), [collective](<https://devfeed.tech/tags/collective.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [groq](<https://devfeed.tech/tags/groq.md>), [groq-3-lpx](<https://devfeed.tech/tags/groq-3-lpx.md>), [inference-performance](<https://devfeed.tech/tags/inference-performance.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>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rubin-gpu](<https://devfeed.tech/tags/rubin-gpu.md>), [speed](<https://devfeed.tech/tags/speed.md>), [systems](<https://devfeed.tech/tags/systems.md>), [tokens](<https://devfeed.tech/tags/tokens.md>), [training-ai-models](<https://devfeed.tech/tags/training-ai-models.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

NVIDIA Groq 3 LPX, paired with Vera Rubin NVL72, delivers high-interactivity AI inference for long-context workloads. A reported benchmark measured 3,431 output tokens per second on Gemma 4 31B with a 100K context.

### Source excerpt

NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform. At the core of the platform is NVIDIA Vera Rubin NVL72, the...

## 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...

## 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...

## Real-time streaming for the agentic era with NVIDIA

DevFeed: [Real-time streaming for the agentic era with NVIDIA](<https://devfeed.tech/articles/real-time-streaming-for-the-agentic-era-with-nvidia-12719.md>)

Original publisher: [Read original article](<https://www.redpanda.com/blog/nvidia-ai-ecosystem>)

Author: Melissa Czapiga

Published: 2026-06-01T00:00:00Z

Content type: article

Language: en

Sources: [Redpanda](<https://devfeed.tech/sources/redpanda.md>)

Topics: [Vera CPU](<https://devfeed.tech/topics/vera-cpu.md>), [streaming-data-processing](<https://devfeed.tech/topics/streaming-data-processing.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Data Infrastructure](<https://devfeed.tech/topics/data-infrastructure.md>), [agent observability](<https://devfeed.tech/topics/agent-observability.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agents](<https://devfeed.tech/tags/agents.md>), [announcement](<https://devfeed.tech/tags/announcement.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data-infrastructure](<https://devfeed.tech/tags/data-infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [systems](<https://devfeed.tech/tags/systems.md>)

### AI overview

Redpanda describes its collaboration with NVIDIA to run streaming workloads on NVIDIA Vera CPUs, reporting 5.5x lower latency for AI agents in mission-critical environments. The article discusses testing on workloads processing billions of messages daily, real-time data infrastructure, and potential benefits for enterprise AI and agentic applications.

### Source excerpt

NVIDIA Vera launches today with Redpanda as part of the ecosystem, delivering 5.5x lower latencies for agents running in mission-critical environments.

## Redpanda pushes the envelope on NVIDIA Vera

DevFeed: [Redpanda pushes the envelope on NVIDIA Vera](<https://devfeed.tech/articles/redpanda-pushes-the-envelope-on-nvidia-vera-12720.md>)

Original publisher: [Read original article](<https://www.redpanda.com/blog/nvidia-vera-cpu-performance-benchmark>)

Author: Travis Downs

Published: 2026-03-16T00:00:00Z

Content type: article

Language: en

Sources: [Redpanda](<https://devfeed.tech/sources/redpanda.md>)

Topics: [NVIDIA Vera](<https://devfeed.tech/topics/nvidia-vera.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>)

Tags: [benchmark](<https://devfeed.tech/tags/benchmark.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [latency](<https://devfeed.tech/tags/latency.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>), [streaming](<https://devfeed.tech/tags/streaming.md>)

### AI overview

Redpanda benchmarks NVIDIA Vera against five other systems on Kafka-compatible streaming workloads. Vera delivers the lowest streaming latencies, better interconnect scaling, faster build times, and up to 73% higher throughput than AMD EPYC "Turin," with the article positioning it for data-intensive enterprise, AI, and agentic workloads.

### Source excerpt

NVIDIA Vera provides 5.5x lower latencies and up to 73% higher throughputs than other leading CPU models.