Tagged "hardware-selection"
10 articles tagged hardware-selection, 30 March 2026 to 30 July 2026. Newest first.
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Building a Dual V100 AI Workstation for Local LLMs
A practical guide to constructing a high-performance local LLM inference workstation using dual NVIDIA V100 GPUs, providing both cost-effective and capable hardware for serious local deployment work.
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CPU vs GPU vs NPU: Which Semiconductor Does What?
A technical breakdown comparing CPUs, GPUs, and NPUs (Neural Processing Units) and their respective roles in AI inference. This educational piece helps practitioners understand hardware trade-offs when selecting platforms for local LLM deployment.
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AMD Advancing AI 2026: Enterprise AI Architecture Basics for Startup Founders
AMD is providing enterprise AI architecture guidance focused on practical deployment patterns. The content addresses foundational architecture decisions for startups building AI systems, including considerations for local and edge inference infrastructure.
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Nvidia Isn't the Only Choice for Local LLMs Anymore, and AMD Test Proves It
A practical benchmark demonstrates that AMD GPUs are now competitive for running local LLMs, challenging Nvidia's dominance and expanding hardware options for self-hosted inference.
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AI Inference is Rewriting the GPU Buying Playbook
A comprehensive analysis of how the emergence of local AI inference is fundamentally changing GPU purchasing decisions and hardware optimization priorities.
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Free Tool Helps Match Local AI Models to Your Hardware
A new free tool eliminates the guesswork from selecting local AI models by automatically analyzing your hardware capabilities and recommending compatible models for optimal performance.
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5 Things I Wish Someone Had Told Me Before I Tried Self-Hosting a Local LLM
A practical guide sharing key lessons learned from self-hosting local LLMs, covering pitfalls and best practices that can accelerate the learning curve for practitioners new to on-device inference. The article distills common mistakes and recommendations from real-world deployment experience.
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GPUs vs. TPUs: Decoding the Powerhouses of AI
A comprehensive comparison of GPU and TPU architectures for AI workloads, examining trade-offs between general-purpose graphics processors and tensor-optimized units for local and edge LLM deployment scenarios.
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Intel's $949 GPU has 32GB of VRAM for local AI, but the software is why Nvidia keeps winning
Intel's new discrete GPU offers compelling hardware specs for local AI workloads at competitive pricing, but software ecosystem and driver maturity remain critical challenges compared to Nvidia's dominance.
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Select the Right Hardware for Your Local LLM Deployment with This Online Guide
An authoritative guide for choosing appropriate hardware for local LLM inference, helping practitioners match their deployment needs to cost-effective hardware solutions.