text model · EXAONE · Windows

Can I run EXAONE 4.0 32B on 32GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine

Yes, it runs slow on this hardware ~2 tok/s est.

Yes. EXAONE 4.0 32B runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~20.2 GB of ~28 GB usable).

Needs ~20.2 GB Device usable ~28 GB

Runs at Q4_K_M using ~20.2 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 ~7.8 GB of headroom.

Q4_K_M needed: ~20.2 GB
Usable on device: ~28 GB
Device memory: 32 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~28 GB usable

Q2_K

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~20.2 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~33.9 GB

FP16

~66.2 GB

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

Running cost · estimate

Power & economics est.

Power draw: ~28 W
Electricity / 1M tokens: ~$0.58

At ~$0.15/kWh and the estimated ~2 tok/s, a million generated tokens costs about $0.58 in electricity. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 2 load the same Q4_K_M weights.

llama.cpp

$ llama-cli -hf LGAI-EXAONE/EXAONE-4.0-32B-GGUF:Q4_K_M

LM Studio

$ lms get LGAI-EXAONE/EXAONE-4.0-32B-GGUF

How to run it

On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).

Model EXAONE

Parameters: 32B
Q4_K_M size: 18.02 GB
Q8_0 size: 31.67 GB
Context: 131k

Full EXAONE 4.0 32B 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 EXAONE 4.0 32B 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 EXAONE 4.0 32B?

Yes. EXAONE 4.0 32B runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~20.2 GB of ~28 GB usable).

How much memory does EXAONE 4.0 32B need?

32GB RAM Laptop (CPU/iGPU only) has room to spare. At Q4_K_M the weights are ~18.02 GB; with KV cache and runtime overhead, budget ~20.2 GB at a 4k context.

What is the best tool to run EXAONE 4.0 32B 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.

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Markdown

[![EXAONE 4.0 32B on 32GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/badge/exaone-4-32b/laptop-32gb.svg)](https://localmodel.run/can-i-run/exaone-4-32b/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.