Almost every guide I came across suggested the same thing: if you want to run a local LLM, you need a dedicated GPU. I already had a self-hosted AI setup running smoothly on my machine with an Nvidia ...

My local LLM doesn't need its own vision tower to be able to see.

After a 7-year corporate stint, Tanveer found his love for writing and tech too much to resist. An MBA in Marketing and the owner of a PC building business, he writes on PC hardware, technology, and ...

Even an older workstation-class eGPU like the NVIDIA Quadro P2200 delivers dramatically faster local LLM inference than CPU-only systems, with token-generation rates up to 8x higher. Running LLMs ...

As the demand for local AI workflows grows, understanding the differences between Neural Processing Units (NPUs) and Graphics Processing Units (GPUs) is increasingly important. NPUs are designed for ...

While many organizations rely on public cloud services for large language models, there are compelling reasons to run these models in-house, within an organization's own data center. Organizations ...

Local AI tools are more powerful than ever, but most of the magic ain't happening on NPUs—much to Microsoft's disappointment, I'm sure. For the last few years, the term “AI PC” has basically meant ...

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Google's Pixel 11 phone uses a Tensor G6 processor with a powerful TPU. How is it different from a GPU, and what does that mean in real-world use?