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Technology#AI Hardware📝 BlogAnalyzed: Dec 29, 2025 01:43

Self-hosting LLM on Multi-CPU and System RAM

Published:Dec 28, 2025 22:34
1 min read
r/LocalLLaMA

Analysis

The Reddit post discusses the feasibility of self-hosting large language models (LLMs) on a server with multiple CPUs and a significant amount of system RAM. The author is considering using a dual-socket Supermicro board with Xeon 2690 v3 processors and a large amount of 2133 MHz RAM. The primary question revolves around whether 256GB of RAM would be sufficient to run large open-source models at a meaningful speed. The post also seeks insights into expected performance and the potential for running specific models like Qwen3:235b. The discussion highlights the growing interest in running LLMs locally and the hardware considerations involved.
Reference

I was thinking about buying a bunch more sys ram to it and self host larger LLMs, maybe in the future I could run some good models on it.

Hardware#AI Hardware📝 BlogAnalyzed: Dec 27, 2025 02:30

Absurd: 256GB RAM More Expensive Than RTX 5090, Will You Pay for AI?

Published:Dec 26, 2025 03:42
1 min read
机器之心

Analysis

This headline highlights the increasing cost of high-capacity RAM, driven by the demands of AI applications. The comparison to the RTX 5090, a high-end graphics card, emphasizes the magnitude of this price increase. The article likely explores the reasons behind this trend, such as increased demand for memory in AI training and inference, supply chain issues, or strategic pricing by memory manufacturers. It also raises the question of whether consumers and businesses are willing to bear these costs to participate in the AI revolution. The article probably discusses the implications for different stakeholders, including AI developers, hardware manufacturers, and end-users.
Reference

N/A