Guide Matches Local LLMs to RAM Sizes: Best Ollama Picks for 4GB to 32GB in 2026

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A new guide ranks the best locally run language models for machines with 4GB, 8GB, 16GB, and 32GB of RAM, based on the authors' testing on real hardware. It explains that models quantized to Q4 need roughly 0.6 to 0.7 GB per billion parameters, plus 1 to 3 GB of overhead for context and the KV cache. The authors argue that newer small models have improved enough that older recommendations are now misleading. For GPU users, the guide notes that available VRAM is the main constraint and that GPU offloading generates text several times faster than CPU inference. Each RAM tier is paired with specific model suggestions and expected speeds, such as roughly 6 to 10 tokens per second on CPU for a 14B model.

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