How much memory does a local LLM need?
Before downloading a model to run it locally, you need to know if it will fit in memory. The estimate is the sum of three terms, compared to what the machine can actually give to the model: need = weights + KV cache + overhead fits if need ≤ 0.8 × usable memory The figures below follow the estimation used by the local model browser of the desktop application…
An article discusses estimating the memory required to run AI models locally. The estimation involves calculating the model's weights, KV cache, and overhead, and comparing it to the device's available memory. For example, a 14B model in Q4_K_M requires around 8-9 GB of memory, with an estimated 8.4 GB displayed by the osFoundry desktop application on a 16 GB MacBook M3. The article provides guidelines for determining whether a model can run on a device based on its memory usage and estimated generation speed.
Written by urgent.news from Dev.to's report — not a translation of it. Machine-written — may contain errors; check the original before relying on it.
