text model · Granite · Windows
Can I run Granite 4.0 H Small on 32GB RAM Laptop (CPU/iGPU only)?
Yes. Granite 4.0 H Small runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~20.4 GB of ~28 GB usable).
Runs at Q4_K_M using ~20.4 GB of ~28 GB usable.
- Q4_K_M needed
- ~20.4 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 granite4:small-h llama-cli -hf unsloth/granite-4.0-h-small-GGUF:Q4_K_M lms get unsloth/granite-4.0-h-small-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 32B (MoE, 9B active)
- Q4_K_M size
- 18.23 GB
- Q8_0 size
- 31.91 GB
- Context
- 128k
- Ollama tag
- granite4:small-h
- Memory
- 32 GB ram
- Usable for weights
- ~28 GB
- Best runtime
- Ollama (llama.cpp backend)
You could also run
Run Granite 4.0 H Small on other hardware
FAQ
Can 32GB RAM Laptop (CPU/iGPU only) run Granite 4.0 H Small?
Yes. Granite 4.0 H Small runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~20.4 GB of ~28 GB usable).
How much memory does Granite 4.0 H Small need?
32GB RAM Laptop (CPU/iGPU only) has room to spare. At Q4_K_M the weights are ~18.23 GB; with KV cache and runtime overhead, budget ~20.4 GB at a 4k context. It is a Mixture-of-Experts model (32B total / 9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Granite 4.0 H Small 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.