Puget Systems

@PugetSystems

Puget Systems blends the roles of system integrator, consultant, and workflow expert to provide our customers with tailor-made workstations and servers.

Seattle, WA bsky.app/profile/pugets… Joined November 2008

423 Following 24K Followers 13K Posts

Latest posts 5

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Puget Systems @PugetSystems Feb 5, 2025

Hey Puget Systems fans!

Starting today we will be shifting our focus to Bluesky. If you'd like to continue following us, receiving our content and engaging in discussions around all things tech, industry and workflows, please follow us over there!
bsky.app/profile/pugets…

Puget Systems @PugetSystems Jan 22, 2025

What's something you wish your workstation or overall set up had that would dramatically change your productivity/creativity? Dream big!

Puget Systems @PugetSystems Jan 22, 2025

Are Intel's Core Ultra 200S CPUs ready to meet the demands of your workflow?
Dive into our detailed content creation review and learn everything you need to make the best decision for your needs. hubs.ly/Q0332W7S0

www.pugetsystems.com Intel Core Ultra 200S Content Creation Review We examine the performance of Intel's new Core Ultra 200S series desktop processors in content creation applications.

Puget Systems @PugetSystems Jan 22, 2025

The NVIDIA GeForce RTX™ 50 Series is almost here!
Whether you're creating stunning visuals or building complex 3D environments, these GPUs are designed to meet the needs of demanding workflows.
Sign up to get notified when they're available: hubs.ly/Q0332-Y20

www.pugetsystems.com NVIDIA GeForce RTX 50 Series A new generation of GeForce RTX™ video cards, powered by NVIDIA's Blackwell GPU architecture, brings the latest in ray tracing, video editing, and AI to gamers and creators.

Puget Systems @PugetSystems Jan 22, 2025

How do GPUs handle large language models of different sizes?
We explore the performance benchmarks to help you choose the best GPU for your AI-assisted workflows. Check it out in this article: hubs.ly/Q0332_Mn0

www.pugetsystems.com Exploring GPU Performance Across LLM Sizes Does the size of a Large Language Model affect relative performance when testing a variety of GPUs?