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Hardware Corner

Hardware Corner

We search the Web for the best refurbished computers. Find out what laptop or desktop suites you the most and what to look fore in recertified computer.

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COMPUTER HARDWARE AND ARCHITECTURE
Is the 48 GB Mac Mini M4 Pro Good for Local LLMs?
If you want to stay in the Apple ecosystem and need a compact system for running local large language models, the Mac Mini with the M4 Pro and 48 GB of unified memory is currently the lowest configuration that makes practical sense. Apple also offers 24 GB versions of the Mac Mini, but they are […]
MAC MINIAPPLE
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HIGH PERFORMANCE COMPUTING
What GPU for Running OpenClaw Locally
Running OpenClaw locally is not the same as running a simple chat model. Once you move into agentic workflows with tool calling, long system prompts, and multi-step reasoning, the hardware requirements shift in a very specific way. VRAM becomes the primary constraint, memory bandwidth defines responsiveness, and model size directly affects reliability. This article focuses […]
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CLOUD COMPUTING AND DISTRIBUTED SYSTEMS
OpenClaw (local) — Hardware and LLM Overview
OpenClaw is a personal, self-hosted AI assistant platform designed to run on your own hardware while connecting to the communication tools you already use. Instead of being just a chat interface, it functions as an agent system—capable of reasoning, executing tasks, and interacting with software and services across multiple steps. A typical OpenClaw setup includes […]
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COMPUTER HARDWARE AND ARCHITECTURE
Best LLM for MacBook Pro with M5 Max and 32GB
The MacBook Pro M5 Max with 32GB unified memory sits in an interesting spot for local LLM inference. It is not a maxed out configuration, but it is the minimum tier where modern 25B to 32B class models start to feel usable for real work. This article focuses on what actually runs, what is worth […]
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MICROPROCESSORS AND CHIPSETS
What Hardware for Gemma 4 26B and 31B LLM Local Use
The new Gemma 4 models from Google DeepMind have landed, and for local LLM users this is one of the more practical releases in a while. The lineup gives us two interesting mid-size targets: a 26B MoE model (A4B) and a 31B dense model. Both support up to 256K context, tool calling, and personal agent-style […]
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