# OLMo 2 32B Instruct: RAM and VRAM requirements

> OLMo 2 32B Instruct is a 32B OLMo model. At Q4_K_M it needs about **21.7 GB** to run and fits **12 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 | 19.5 GB | ~21.7 GB |
| Q8_0 | 34.3 GB | ~36.5 GB |
| FP16 | 64.5 GB | ~66.7 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, but tight
- **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/olmo-2-32b

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

## Details
- Parameters: 32B
- Default context: 4k tokens
- License: Apache-2.0 (commercial use: yes)
- Released: 2025-03
- HuggingFace: 5,027 downloads/mo, 147 likes

## FAQ
### How much VRAM or RAM does OLMo 2 32B Instruct need?
About 21.7 GB at Q4_K_M (weights 19.5 GB + KV cache + overhead) at a 4k context. Budget ~36.5 GB for Q8_0.
### Can OLMo 2 32B Instruct run on a laptop?
OLMo 2 32B Instruct is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use OLMo 2 32B Instruct commercially?
Yes, Apache-2.0 permits commercial use.

Sources: https://huggingface.co/allenai/OLMo-2-0325-32B-Instruct, https://huggingface.co/allenai/OLMo-2-0325-32B/blob/main/config.json, https://huggingface.co/unsloth/OLMo-2-0325-32B-Instruct-GGUF, https://huggingface.co/allenai/OLMo-2-0325-32B-Instruct-GGUF, https://ollama.com/library/olmo2/tags
More: https://localmodel.run/model/olmo-2-32b