One Command to Check How Ready Your System Is for Local AI

If you’re running local AI tools like Ollama, Jan, LM Studio or llama.cpp, one of the first things you’ll want to know is whether your GPU is up to the task. VRAM size, compute capability, and driver support all play a big role in whether models will r…


This content originally appeared on DEV Community and was authored by Daniel Chifamba

If you’re running local AI tools like Ollama, Jan, LM Studio or llama.cpp, one of the first things you’ll want to know is whether your GPU is up to the task. VRAM size, compute capability, and driver support all play a big role in whether models will run smoothly (or crash out of memory).

A neat shortcut: if you have Node.js installed, you can run:

npx —-yes node-llama-cpp inspect gpu

Even though this command comes from node-llama-cpp, the output is universally useful. It quickly reports your OS, GPU, CPU, RAM, and driver metrics— that apply no matter which local AI framework you’re using.

Sample Output
Sample output of AI metrics

With this quick check, you’ll know exactly what your machine can handle, and can better choose the right models and settings for your local AI experiments.


This content originally appeared on DEV Community and was authored by Daniel Chifamba


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Daniel Chifamba | Sciencx (2025-08-24T09:44:28+00:00) One Command to Check How Ready Your System Is for Local AI. Retrieved from https://www.scien.cx/2025/08/24/one-command-to-check-how-ready-your-system-is-for-local-ai/

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