Strix Halo
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Apr. 2, 2026 / Hardware Insights
Best Laptop for Running OpenClaw AI Agent Locally
Running OpenClaw locally is very different from running a chat UI. If you have already read guides like Best Mini Computer for Running OpenClaw AI Agent and Understanding OpenClaw Hardware Requirements, you know the bottleneck is not just loading a model. It is sustaining long agent loops with tool calls, large context, and repeated prompt...
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Mar. 31, 2026 / Hardware Insights
Best Mini Computer (PC/Mac) for Running OpenClaw AI Agent
Understanding OpenClaw Hardware Requirements OpenClaw is not a typical chat interface. It is an agentic system that continuously executes tools, runs shell commands, sets cron jobs, and manages files. This changes the hardware profile significantly. The main constraint is not just model size, but consistency. Agentic workflows require models that can follow tool calls, maintain...
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Jan. 26, 2026 / Hardware Insights
Best Computers for Running ClawdBot (OpenClaw) AI Assistant Locally
If you are running OpenClaw with a cloud model like Claude Opus, you do not need powerful hardware. Any modern low power system with 8 GB of RAM and a 6th+ gen Intel CPU is enough. If you want to run ClawdBot fully local with reliable tool usage and large context windows, hardware requirements scale...
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Jan. 19, 2026 / Hardware Insights
Ryzen AI Halo Is Not New Hardware – It’s AMD’s Strix Halo AI Developer Platform
AMD Ryzen AI Halo is being marketed as a new local AI development solution, but it is important to be precise about what it actually is. Ryzen AI Halo does not introduce new silicon, new performance characteristics, or a faster variant of Strix Halo. It is a reference mini PC platform built around the already...
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Dec. 9, 2025 / Hardware Insights
Best Unified Memory Computers for Local LLMs (2025): Bandwidth, Memory Size, Speed & Price Comparison
Unified memory has become one of the most important features for anyone running local LLMs in 2025. Instead of splitting memory between CPU RAM and GPU VRAM, unified architectures pool it into one high-bandwidth space that both the CPU and GPU can access. This matters because LLM inference is memory-bound long before it becomes compute-bound....
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Oct. 11, 2025 / Hardware Insights
What Makes Apple Silicon and Strix Halo Good at Running Local LLMs?.
For years, the formula for running large language models locally has been simple: get as much VRAM as you can afford. This usually meant building complex, power-hungry desktop rigs with multiple GPUs or hunting for deals on used server hardware. But a new class of hardware, powered by Apple Silicon and AMD’s “Strix Halo” APUs,...
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Oct. 8, 2025 / How to Run LLMs Localy
I optimized my Strix Halo for local LLMs: Here are the benchmarks and findings.
If you’ve gotten your hands on an AMD Ryzen AI Max+ 395 (Strix Halo) system, you already know the raw hardware is impressive. That massive pool of unified LPDDR5x memory is a game-changer for running large models locally. But unlocking its full potential isn’t just plug-and-play. The key to getting the best possible performance lies...
