A compiled guide from a year of local LLM experiments covers llama.cpp tuning across VRAM fitting, KV cache configuration, MoE layer placement, multi-token prediction, CPU offloading, and common OOM failure modes. Targets practitioners running inference on consumer or prosumer hardware.
HOW THIS AFFECTS YOU
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builderYou can use this as a reference checklist when deploying local models, particularly for avoiding OOM errors and tuning MoE placement on memory-constrained setups.