32GB RAM helps, but VRAM matters more.

Yes, but it depends on whether you’re running on CPU or GPU.

For CPU inference (like llama.cpp or Ollama), 32GB is plenty. A 7B model in 4-bit quantization uses about 4-6GB of system RAM, leaving plenty of room for context and multitasking. If you’re going that route, 32GB is a sweet spot.

For GPU inference, VRAM is the bottleneck. A 7B model in 4-bit needs around 6-8GB of VRAM. Full precision can use 14GB+. 32GB system RAM won’t help there unless you’re offloading layers from