# NVL72

Published articles for NVL72.

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

## NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

DevFeed: [NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut](<https://devfeed.tech/articles/nvidia-vera-rubin-nvl72-delivers-leading-performance-in-mlperf-inference-v6-1-debut-31524.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/vera-rubin-nvl72-mlperf-inference/>)

Author: Zhihan Jiang

Published: 2026-09-16T15:00:48Z

Content type: article

Language: en

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

Topics: [NVIDIA Vera Rubin](<https://devfeed.tech/topics/nvidia-vera-rubin.md>), [Vera Rubin NVL72](<https://devfeed.tech/topics/vera-rubin-nvl72.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [Dynamo](<https://devfeed.tech/topics/dynamo.md>), [vllm](<https://devfeed.tech/topics/vllm.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [TensorRT-LLM](<https://devfeed.tech/topics/tensorrt-llm.md>)

Tags: [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [dynamo](<https://devfeed.tech/tags/dynamo.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [inference](<https://devfeed.tech/tags/inference.md>), [mlperf](<https://devfeed.tech/tags/mlperf.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [software](<https://devfeed.tech/tags/software.md>), [tensorrt](<https://devfeed.tech/tags/tensorrt.md>), [tensorrt-llm](<https://devfeed.tech/tags/tensorrt-llm.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

### AI overview

NVIDIA reports MLPerf Inference v6.1 preview results for Vera Rubin NVL72 and GB300 NVL72 systems. Vera Rubin NVL72 delivered up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and up to 2.5x higher throughput on DeepSeek-R1, while a four-rack GB300 NVL72 submission achieved 99% scaling efficiency. The results used vLLM, NVIDIA Dynamo, and TensorRT-LLM.

### Source excerpt

System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments. [...]

## How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin

DevFeed: [How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin](<https://devfeed.tech/articles/how-nvidia-groq-3-lpx-deterministic-execution-drives-power-efficient-high-interactivity-inference-on-nvidia-vera-rubin-26913.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/how-nvidia-groq-3-lpx-deterministic-execution-drives-power-efficient-high-interactivity-inference-on-nvidia-vera-rubin/>)

Author: Tanya Lenz

Published: 2026-09-15T16:55:00Z

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: [Groq 3 LPX](<https://devfeed.tech/topics/groq-3-lpx.md>), [LPX](<https://devfeed.tech/topics/lpx.md>), [NVIDIA Vera Rubin](<https://devfeed.tech/topics/nvidia-vera-rubin.md>), [Vera Rubin NVL72](<https://devfeed.tech/topics/vera-rubin-nvl72.md>), [groq](<https://devfeed.tech/topics/groq.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Low Latency](<https://devfeed.tech/topics/low-latency.md>), [long-context](<https://devfeed.tech/topics/long-context.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [ai-platform](<https://devfeed.tech/tags/ai-platform.md>), [drive](<https://devfeed.tech/tags/drive.md>), [dsx](<https://devfeed.tech/tags/dsx.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>), [inference-performance](<https://devfeed.tech/tags/inference-performance.md>), [latency](<https://devfeed.tech/tags/latency.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [lpx](<https://devfeed.tech/tags/lpx.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [power-management](<https://devfeed.tech/tags/power-management.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

This NVIDIA developer article explains how Groq 3 LPX uses deterministic execution across 256 LPU chips to support low-latency inference on NVIDIA Vera Rubin. It describes compiler-scheduled execution and power-management techniques including Preemptive Power and Clock Period Synthesis.

### Source excerpt

Power is a defining constraint for AI factories. As AI workloads demand a full compute platform to serve them, each component of that platform must maximize...

## From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry

DevFeed: [From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry](<https://devfeed.tech/articles/from-wafer-out-to-first-token-codifying-supply-chain-expertise-with-nemotron-and-palantir-foundry-6824.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/from-wafer-out-to-first-token-codifying-supply-chain-expertise-with-nemotron-and-palantir-foundry/>)

Author: Elizabeth Goodman

Published: 2026-09-10T09:00:00Z

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: [datacenter](<https://devfeed.tech/topics/datacenter.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Software](<https://devfeed.tech/topics/software.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [compute](<https://devfeed.tech/tags/compute.md>), [cuopt](<https://devfeed.tech/tags/cuopt.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [llms](<https://devfeed.tech/tags/llms.md>), [manufacturing](<https://devfeed.tech/tags/manufacturing.md>), [memory](<https://devfeed.tech/tags/memory.md>), [nemo](<https://devfeed.tech/tags/nemo.md>), [nemotron](<https://devfeed.tech/tags/nemotron.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-blackwell](<https://devfeed.tech/tags/nvidia-blackwell.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [production](<https://devfeed.tech/tags/production.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [software](<https://devfeed.tech/tags/software.md>), [supply-chain](<https://devfeed.tech/tags/supply-chain.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

NVIDIA describes how it measures and reduces the time from wafer-out to first token across complex Grace Blackwell and Vera Rubin supply chains. The article focuses on time-to-rack, critical material allocation, real-time visibility, redundancy, reliability, and codifying human expertise.

### Source excerpt

NVIDIA has one of the largest and most complex supply chains in the world, and its performance is measured from wafer-out to first token. The interval is in two...

## 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.

## Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free

DevFeed: [Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free](<https://devfeed.tech/articles/micron-6600-ion-245tb-swap-the-hard-drives-power-an-nvl72-for-free-12385.md>)

Original publisher: [Read original article](<https://www.storagereview.com/review/micron-6600-ion-245tb-swap-the-hard-drives-power-an-nvl72-for-free>)

Author: Brian Beeler

Published: 2026-09-03T17:00:39Z

Content type: article

Language: en

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

Topics: [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [datacenter](<https://devfeed.tech/topics/datacenter.md>), [GB200](<https://devfeed.tech/topics/gb200.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Server](<https://devfeed.tech/topics/server.md>), [dell](<https://devfeed.tech/topics/dell.md>)

Tags: [benchmark](<https://devfeed.tech/tags/benchmark.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [dell](<https://devfeed.tech/tags/dell.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [hdd](<https://devfeed.tech/tags/hdd.md>), [measurements](<https://devfeed.tech/tags/measurements.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [servers](<https://devfeed.tech/tags/servers.md>), [ssd](<https://devfeed.tech/tags/ssd.md>), [storage](<https://devfeed.tech/tags/storage.md>)

### AI overview

This article evaluates replacing eight 30TB nearline HDDs with one 245TB Micron 6600 ION SSD. Its measurements indicate lower power consumption, substantially higher read efficiency, and a reduction from 22 racks of HDD storage to six racks of flash at exabyte scale, potentially freeing enough power for a GB200 NVL72.

### Source excerpt

For two decades, the SSD-versus-HDD conversation ended the same way: flash wins on performance, disk wins on price per terabyte, and the size of that price gap settled the argument in favor of bulk storage. As storage technology has matured and AI has taken over, that framing is clearly out of date. The largest data The post Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free appeared first on StorageReview.com.

## How XPUs Meet a World-Class AI Factory

DevFeed: [How XPUs Meet a World-Class AI Factory](<https://devfeed.tech/articles/how-xpus-meet-a-world-class-ai-factory-6958.md>)

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

Author: Jesse Clayton

Published: 2026-08-24T15:00:54Z

Content type: article

Language: en

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

Topics: [AI Factory](<https://devfeed.tech/topics/ai-factory.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [Network](<https://devfeed.tech/topics/network.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Low Latency](<https://devfeed.tech/topics/low-latency.md>), [moe](<https://devfeed.tech/topics/moe.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [AI Platform](<https://devfeed.tech/topics/ai-platform.md>), [Latency](<https://devfeed.tech/topics/latency.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [ecosystem](<https://devfeed.tech/tags/ecosystem.md>), [ethernet](<https://devfeed.tech/tags/ethernet.md>), [gb300-nvl72](<https://devfeed.tech/tags/gb300-nvl72.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [mixture-of-experts](<https://devfeed.tech/tags/mixture-of-experts.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia-dsx](<https://devfeed.tech/tags/nvidia-dsx.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [software](<https://devfeed.tech/tags/software.md>), [time](<https://devfeed.tech/tags/time.md>), [xpu](<https://devfeed.tech/tags/xpu.md>)

### AI overview

The article explains how NVLink Fusion combines custom XPUs with NVIDIA's established AI infrastructure to help build semi-custom AI factories. It focuses on scale-up networking, performance, resiliency, telemetry, platform maturity, and the economics of large-scale AI workloads.

### Source excerpt

To generate intelligence at scale, AI factories run continuously, and their economics are defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime. That requires AI infrastructure designed and built as a full factory, not a collection of individual accelerators. Hyperscalers and AI-native companies building custom XPUs must consider [...]

## 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 Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure

DevFeed: [NVIDIA Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure](<https://devfeed.tech/articles/nvidia-exemplar-cloud-lessons-for-unlocking-full-performance-on-ai-infrastructure-6891.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-exemplar-cloud-lessons-for-unlocking-full-performance-on-ai-infrastructure/>)

Author: Elizabeth Goodman

Published: 2026-07-30T16:00:00Z

Content type: tutorial

Language: en

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

Topics: [debugging](<https://devfeed.tech/topics/debugging.md>), [Processes](<https://devfeed.tech/topics/processes.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cloud-services](<https://devfeed.tech/tags/cloud-services.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [debugging](<https://devfeed.tech/tags/debugging.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [dgx-cloud](<https://devfeed.tech/tags/dgx-cloud.md>), [diagnostics](<https://devfeed.tech/tags/diagnostics.md>), [distributed-training](<https://devfeed.tech/tags/distributed-training.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gb300-nvl72](<https://devfeed.tech/tags/gb300-nvl72.md>), [grace-cpu](<https://devfeed.tech/tags/grace-cpu.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [infiniband](<https://devfeed.tech/tags/infiniband.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [kernel](<https://devfeed.tech/tags/kernel.md>), [linux](<https://devfeed.tech/tags/linux.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [training](<https://devfeed.tech/tags/training.md>)

### AI overview

A troubleshooting guide for closing AI-training throughput gaps between NVIDIA reference architectures and partner clusters. It covers configuration and installation issues across memory management, CPU power and NUMA placement, NCCL queue-pair concurrency, and hardware setup.

### Source excerpt

Two AI computing clusters built from identical NVIDIA H100, GB200 NVL72, or GB300 NVL72 systems can deliver materially different training throughput. We...

## Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72

DevFeed: [Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72](<https://devfeed.tech/articles/setting-a-world-record-for-moe-pre-training-on-nvidia-gb300-nvl72-6939.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/setting-a-world-record-for-moe-pre-training-on-nvidia-gb300-nvl72/>)

Author: Kirthi Devleker

Published: 2026-07-21T18:30:00Z

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: [Mixture of Experts (MoE)](<https://devfeed.tech/topics/mixture-of-experts-moe.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [AI Platform](<https://devfeed.tech/topics/ai-platform.md>), [NCCL](<https://devfeed.tech/topics/nccl.md>), [networking](<https://devfeed.tech/topics/networking.md>), [deepseek](<https://devfeed.tech/topics/deepseek.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-platform](<https://devfeed.tech/tags/ai-platform.md>), [ai-training](<https://devfeed.tech/tags/ai-training.md>), [collective](<https://devfeed.tech/tags/collective.md>), [communication](<https://devfeed.tech/tags/communication.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [deepseek](<https://devfeed.tech/tags/deepseek.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [featured](<https://devfeed.tech/tags/featured.md>), [frontier-model](<https://devfeed.tech/tags/frontier-model.md>), [gb300-nvl72](<https://devfeed.tech/tags/gb300-nvl72.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llm-techniques](<https://devfeed.tech/tags/llm-techniques.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [megatron](<https://devfeed.tech/tags/megatron.md>), [mixture-of-experts-moe](<https://devfeed.tech/tags/mixture-of-experts-moe.md>), [moe](<https://devfeed.tech/tags/moe.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [train](<https://devfeed.tech/tags/train.md>), [training-ai-models](<https://devfeed.tech/tags/training-ai-models.md>)

### AI overview

The article explains how NVIDIA GB300 NVL72 achieved a world record for DeepSeek-V3 671B mixture-of-experts pre-training. It focuses on the communication demands of MoE models, including all-to-all traffic between GPUs, and the need for tightly coupled scale-up and predictable scale-out networking to sustain delivered training performance.

### Source excerpt

Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token...

## Reducing High-Bandwidth Memory Bottlenecks in JAX-Based LLM Training with Host Offloading

DevFeed: [Reducing High-Bandwidth Memory Bottlenecks in JAX-Based LLM Training with Host Offloading](<https://devfeed.tech/articles/reducing-high-bandwidth-memory-bottlenecks-in-jax-based-llm-training-with-host-offloading-6925.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/reducing-high-bandwidth-memory-bottlenecks-in-jax-based-llm-training-with-host-offloading/>)

Author: Tanya Lenz

Published: 2026-07-10T18:17:40Z

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: [LLM Techniques](<https://devfeed.tech/topics/llm-techniques.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Mixture of Experts (MoE)](<https://devfeed.tech/topics/mixture-of-experts-moe.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [compute](<https://devfeed.tech/tags/compute.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [grace-cpu](<https://devfeed.tech/tags/grace-cpu.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llm-techniques](<https://devfeed.tech/tags/llm-techniques.md>), [mixture-of-experts-moe](<https://devfeed.tech/tags/mixture-of-experts-moe.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>), [training-ai-models](<https://devfeed.tech/tags/training-ai-models.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [work](<https://devfeed.tech/tags/work.md>)

### AI overview

This article explains how host offloading in JAX-based large language model training reduces GPU high-bandwidth memory pressure by moving selected activations to pinned host memory and streaming them back during the backward pass. It discusses activation-transfer overlap, NVIDIA Grace Blackwell and GB200 NVL72 systems, and experiments involving Llama 3.1 405B and DeepSeek-V3 671B.

### Source excerpt

Large language model (LLM) training workloads increasingly run into GPU memory limits before compute is fully used. Model weights, gradients, optimizer states,...

## Running Low-Latency Analytical Workloads with GPU-Accelerated Presto on NVIDIA GB200 NVL72

DevFeed: [Running Low-Latency Analytical Workloads with GPU-Accelerated Presto on NVIDIA GB200 NVL72](<https://devfeed.tech/articles/running-low-latency-analytical-workloads-with-gpu-accelerated-presto-on-nvidia-gb200-nvl72-6935.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/running-low-latency-analytical-workloads-with-gpu-accelerated-presto-on-nvidia-gb200-nvl72/>)

Author: Tanya Lenz

Published: 2026-07-08T16:05:25Z

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: [GPU](<https://devfeed.tech/topics/gpu.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [SQL](<https://devfeed.tech/topics/sql.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [GPUDirect](<https://devfeed.tech/topics/gpudirect.md>), [NVIDIA DGX](<https://devfeed.tech/topics/nvidia-dgx.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [parquet](<https://devfeed.tech/topics/parquet.md>), [C++](<https://devfeed.tech/topics/c-plus-plus.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>)

Tags: [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [cache](<https://devfeed.tech/tags/cache.md>), [communication](<https://devfeed.tech/tags/communication.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data](<https://devfeed.tech/tags/data.md>), [data-analytics](<https://devfeed.tech/tags/data-analytics.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpudirect](<https://devfeed.tech/tags/gpudirect.md>), [latency](<https://devfeed.tech/tags/latency.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [multi-gpu](<https://devfeed.tech/tags/multi-gpu.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-dgx](<https://devfeed.tech/tags/nvidia-dgx.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [performance](<https://devfeed.tech/tags/performance.md>)

### AI overview

This article presents GPU-accelerated Presto for low-latency analytical SQL workloads on large datasets. It compares single-node multi-GPU execution on NVIDIA DGX B200 and multinode NVIDIA GB200 NVL72 systems with CPU-based Presto, highlighting NVLink communication, GPUDirect Storage, cuDF algorithms, Parquet data, and benchmark results.

### Source excerpt

Presto is an open source, distributed SQL engine for running fast, interactive queries on very large datasets. On NVIDIA GPUs, Presto delivers peak performance...

## I Went to COMPUTEX 2026. Here's What Actually Stood Out.

DevFeed: [I Went to COMPUTEX 2026. Here's What Actually Stood Out.](<https://devfeed.tech/articles/i-went-to-computex-2026-here-s-what-actually-stood-out-10519.md>)

Original publisher: [Read original article](<https://technotim.com/posts/computex-2026/>)

Author: Techno Tim

Published: 2026-06-07T13:00:00Z

Content type: opinion

Language: en

Sources: [Techno Tim](<https://devfeed.tech/sources/techno-tim.md>)

Topics: [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [NVIDIA Research](<https://devfeed.tech/topics/nvidia-research.md>), [pc](<https://devfeed.tech/topics/pc.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Robotics](<https://devfeed.tech/topics/robotics.md>)

Tags: [2026](<https://devfeed.tech/tags/2026.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [pc](<https://devfeed.tech/tags/pc.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [scale](<https://devfeed.tech/tags/scale.md>), [storage](<https://devfeed.tech/tags/storage.md>)

### AI overview

A first-person report from COMPUTEX 2026 describing how thoroughly artificial intelligence dominated the hardware show. The article highlights AI infrastructure, workstations, PCs, NAS and storage, edge devices, servers, factories, agents, and the networking, power, and cooling systems supporting them, with NVIDIA's influence visible across many vendor demonstrations.

### Source excerpt

COMPUTEX 2026 was my first hardware show at this scale, and I went in expecting AI to be a major theme. That part was obvious before I even landed in Taipei. What I didn't expect was how completely it had taken over. Every company at the show was telling an AI story. COMPUTEX 2026 officially ran under the theme "AI Together." It had 1,500 exhibitors from 33 countries, 6,000 booths, and major c...