A 16GB PC can run small local AI models, but a more capable experience usually calls for 32GB of memory or a graphics card with at least 16GB of VRAM. Engadget’s practical guide explains what those numbers mean, and why a model that fits your GPU can respond much faster than one spilling into ordinary system memory.
Watch Desk analysis
What happened
The guide says a typical 16GB computer can handle models with around seven to eight billion parameters. For larger options, it points to at least 32GB of memory and a graphics card with 16GB or more of VRAM. Quantisation can shrink model files, but even a compressed model still has to fit in the available memory to run.
There are useful speed examples, too. Engadget recounts running Mistral 7B on a laptop using Intel’s OpenVINO toolkit: the NPU handled most of the work while CPU use stayed low, and the laptop remained responsive. The same model run through Ollama put much more load on the CPU and memory. These are specific examples, not a guarantee that every laptop or model will behave the same way.
Why it matters
The practical choice is not simply “does my PC have an AI chip?” Memory capacity and bandwidth determine which models fit and how quickly they generate text. Engadget uses five to ten tokens per second as a rough pace for keeping up with most readers, while noting that frontier-scale models remain beyond ordinary PCs.
That gives prospective local-AI users a more useful shopping guide than a badge on a laptop box. A modest machine can be enough for small, private or offline tasks; spending more may buy access to larger models, but not automatically cloud-frontier capability.
Our read
The strongest takeaway is refreshingly unglamorous: check memory before buying into the local-AI dream. A graphics card’s VRAM can make a real difference, but so can software support for a laptop’s NPU. Treat the benchmarks as examples to compare, not promises for your exact setup.
What to watch
- Whether your preferred model fits in the memory available after other applications are running.
- Independent speed tests for the exact hardware and software combination you plan to use.
- Whether new local models deliver enough value to justify the extra memory or graphics-card cost.
Discussion spark: Would you spend extra for a PC that can run larger local models, or is a smaller offline model enough to justify keeping the work on your own machine?
Sources and evidence
- What Hardware Does Your PC Need To Run A Local AI Model? – Engadget (9 November 2026, 13:45 UTC)
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