AI article
LLMs on Consumer Hardware — Part 5: Distributing the Workers and the Memory Budget
Community description: The fifth entry in a build-log series on local LLMs. Moving the workers to a second machine resolves the memory wall and the 120B coordinator runs resident at last; a later collision with GPU image generation shows that a local multi-model system is governed by a memory budget, where placement and right-sizing beat raw capacity.
Dev.to | Oct 14, 2026 | Sven Welack
Automated excerpt
The conclusion was that a coordinator and its workers must fit in memory together. The coordinator claimed about 77 GB of the 80 GB of RAM; image generation needed the GPU and a few gigabytes of RAM of its own. Idle memory pages swap out cheaply; only actively-used memory thrashes.
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