# EXAONE 4.0 32B: RAM and VRAM requirements

> EXAONE 4.0 32B is a 32B EXAONE model. At Q4_K_M it needs about **20.2 GB** to run and fits **13 of 40** tracked devices. Minimum to run: Nvidia GeForce RTX 4090 (24GB).

Last validated: 2026-08-03. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 18.02 GB | ~20.2 GB |
| Q8_0 | 31.67 GB | ~33.9 GB |
| FP16 | 64.01 GB | ~66.2 GB |

Memory = weights + KV cache + ~0.8 GB runtime overhead, and varies ±15% with context length.

## Will it run on my device?
- **Apple M1 (8GB)** (8 GB): No, not enough memory
- **iPhone 17** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): No, not enough memory
- **16GB RAM Laptop (CPU/iGPU only)** (16 GB): No, not enough memory
- **Google Pixel 10 Pro** (16 GB): No, not enough memory
- **Nvidia GeForce RTX 3090 (24GB)** (24 GB): Yes, it runs
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs (room for FP16)

Full table of all 40 devices: https://localmodel.run/model/exaone-4-32b

## How to run
Use LM Studio (Mac/Windows) or Ollama / vLLM (Linux).

## Details
- Parameters: 32B
- Default context: 131k tokens
- License: EXAONE AI Model License Agreement 1.2 - NC (commercial use: no)
- Released: 2025-07
- HuggingFace: 27,223 downloads/mo, 282 likes

## FAQ
### How much VRAM or RAM does EXAONE 4.0 32B need?
About 20.2 GB at Q4_K_M (weights 18.02 GB + KV cache + overhead) at a 4k context. Budget ~33.9 GB for Q8_0.
### Can EXAONE 4.0 32B run on a laptop?
EXAONE 4.0 32B is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use EXAONE 4.0 32B commercially?
No: EXAONE AI Model License Agreement 1.2 - NC: non-commercial / research use only..

Sources: https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B, https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B-GGUF, https://huggingface.co/bartowski/LGAI-EXAONE_EXAONE-4.0-32B-GGUF
More: https://localmodel.run/model/exaone-4-32b