text model · Granite · Windows

Can I run Granite 4.0 H Small on 32GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine

Yes, it runs slow on this hardware

Yes. Granite 4.0 H Small runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~20.3 GB of ~28 GB usable).

Needs ~20.3 GB Device usable ~28 GB

Runs at Q4_K_M using ~20.3 GB of ~28 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. 32GB RAM Laptop (CPU/iGPU only) leaves ~7.7 GB of headroom.

Q4_K_M needed: ~20.3 GB
Usable on device: ~28 GB
Device memory: 32 GB
Best quant: Q4_K_M

Share on X Share on Reddit

Which quant fits

Quant ladder vs ~28 GB usable

Q2_K

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~20.3 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~34.1 GB

FP16

~66.6 GB

The line marks 32GB RAM Laptop (CPU/iGPU only)'s ~28 GB budget; rungs past it are too large.

Run it

Install commands Windows

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run granite4:32b-a9b-h

llama.cpp

$ llama-cli -hf ibm-granite/granite-4.0-h-small-GGUF:Q4_K_M

LM Studio

$ lms get ibm-granite/granite-4.0-h-small-GGUF

Model Granite

Parameters: 32B (MoE, 9B active)
Q4_K_M size: 18.14 GB
Q8_0 size: 31.91 GB
Context: 128k
Ollama tag: granite4:32b-a9b-h

Full Granite 4.0 H Small requirements →

Device Windows

Memory: 32 GB ram
Usable for weights: ~28 GB
Power draw: ~28 W
Best runtime: Ollama (llama.cpp backend)

Best models for 32GB RAM Laptop (CPU/iGPU only) →

You could also run

Run Granite 4.0 H Small on other hardware

Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)Apple M5 (32GB)Apple M4 Pro (48GB)

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 (~20.3 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 ~18.14 GB; with KV cache and runtime overhead, budget ~20.3 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.

Embed this

A live badge for your model card or README, updated as the data is.

Markdown

[![Granite 4.0 H Small on 32GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/badge/granite-4-h-small/laptop-32gb.svg)](https://localmodel.run/can-i-run/granite-4-h-small/laptop-32gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.