text model · llama · Windows
Can I run Llama 3.2 3B on 32GB RAM Laptop (CPU/iGPU only)?
Yes. Llama 3.2 3B runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~3.2 GB of ~28 GB usable).
Runs at Q4_K_M using ~3.2 GB of ~28 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~3.2 GB
- Usable on device
- ~28 GB
- Device memory
- 32 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
ollama run llama3.2:3b llama-cli -hf unsloth/Llama-3.2-3B-Instruct-GGUF:Q4_K_M lms get unsloth/Llama-3.2-3B-Instruct-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 3B
- Q4_K_M size
- 2.02 GB
- Q8_0 size
- 3.42 GB
- Context
- 128k
- Ollama tag
- llama3.2:3b
- Memory
- 32 GB ram
- Usable for weights
- ~28 GB
- Best runtime
- Ollama (llama.cpp backend)
You could also run
Run Llama 3.2 3B on other hardware
FAQ
Can 32GB RAM Laptop (CPU/iGPU only) run Llama 3.2 3B?
Yes. Llama 3.2 3B runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~3.2 GB of ~28 GB usable).
How much memory does Llama 3.2 3B need?
32GB RAM Laptop (CPU/iGPU only) has room to spare. At Q4_K_M the weights are ~2.02 GB; with KV cache and runtime overhead, budget ~3.2 GB at a 4k context.
What is the best tool to run Llama 3.2 3B on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Sources
Memory figures are estimates. See methodology.