Category: AI Stack
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VMware Private AI Reference Architecture and Sizing: A Practical Blueprint (Private AI Series, Part 7)
How to size a VMware Private AI Foundation build the right way: two-domain design, choosing the deployment model, and working from workload back to GPU hosts and BOM on VCF 9.1.
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GPU Partitioning for VMware Private AI: Choosing Between vGPU, MIG and Passthrough (Private AI Series, Part 6)
Time-sliced vGPU, MIG-backed vGPU, GPU passthrough and the new ESXi 9 Update 1 hybrid mode each fit different Private AI workloads. Here is how to design the split, with a capability matrix and a reference topology.
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Choosing the Right GPU for VMware Private AI: L40S vs H100 vs H200 vs Blackwell (Private AI Series, Part 5)
A field-tested guide to picking the GPU for VMware Private AI Foundation: how L40S, H100, H200, RTX PRO 6000 Blackwell and A100 compare, why form factor beats the model name, and a clear verdict on which to choose for RAG, inference or training.
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VMware Private AI Foundation Planning and Prerequisites: GPU Hosts, Drivers and Readiness (Private AI Series, Part 4)
A practitioner’s planning guide for VMware Private AI Foundation with NVIDIA on VCF 9: GPU host selection, the vGPU driver and GPU Operator interoperability matrix, sharing-mode choices, and the readiness checks that decide whether your first deployment lands clean.
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VMware Private AI Foundation Licensing: VCF Add-On vs NVIDIA AI Enterprise (Private AI Series, Part 3)
Private AI Foundation is three licenses, not one: VCF per core, the PAIF add-on per core, and NVIDIA AI Enterprise per GPU. Here is how they stack, what bundles with your GPUs, and the verdict on subscription vs perpetual.
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VMware Private AI Foundation Architecture and Components, Layer by Layer (Private AI Series, Part 2)
VMware Private AI Foundation is five layers, not one box. A reference walk through every PAIF component on VCF 9.1: the GPU platform, DSM with pgvector, Private AI Services, and the single-zone limit you have to design around.
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What VMware Private AI Foundation with NVIDIA Actually Is (Private AI Series, Part 1)
Part 1 of the VMware Private AI Series: a clear, opinionated explainer of what PAIF really is, what it is not, the components that do the work, and when it earns its license on VCF 9.1.
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How to Deploy VMware Private AI Foundation with NVIDIA on VCF 9 (VCF 9 Series, Part 26)
A field-tested runbook for deploying VMware Private AI Foundation with NVIDIA on VCF 9: the two deployment paths, the three licenses you need, GPU host prep, the right sharing mode, and the guided workflow, plus the gotchas that stall bring-up.
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5 GPU & vGPU Mistakes That Break VMware Private AI Foundation (and How to Fix Them)
Most failed VMware Private AI Foundation deployments break on host-side GPU configuration, not the model. Here are five vGPU mistakes in VCF 9.1 and the exact commands to confirm and fix each one.
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Introducing the AI Infrastructure Sizing & Cost Calculator
Over the past few months, I have been spending a lot of time exploring on AI infrastructure around VMware Private AI, NVIDIA AI Enterprise, RAG,
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ML Concepts – Evaluation Matrix and Equations
There are several classifiers can be used to identify the model’s effectiveness. You can assess using the evaluation metrics such as Accuracy, Recall, F1 Score,
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ML Concepts – Loss Function in ANN
The Loss Function is one of the important components of Neural Networks. Loss is nothing but a prediction error of Neural Net. And the method
Architect’s Toolkit
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- AI Infra Sizing & Cost Calculator
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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