OpenClaw, Ollama favor 32GB RAM

Hot take: if you’re choosing one, prioritize 32GB RAM first, especially for coding agents, browser-heavy workflows, and normal development multitasking.

• –Ollama can run small quantized models without huge VRAM demands; the first pain point is usually overall system memory, not raw GPU power.
• –OpenClaw-style agent workflows add overhead from the editor, browser, terminal, background services, and multiple tool processes, which makes 16GB feel cramped fast.
• –A GPU matters most when you already know you want faster token generation and the model fits comfortably in VRAM.
• –On Windows laptops, paging to disk when memory runs out is a worse experience than slower-but-stable CPU or hybrid inference.
• –Best-case setup is both 32GB RAM and a decent RTX GPU, but between your two options, the 32GB thin-and-light is the more practical daily driver for local LLM dev.