---
title: "Can I run an LLM without a GPU?"
description: "Yes, but large models will be slow. Tools such as llama.cpp run on ordinary CPUs, and speed is limited by system memory bandwidth, about 90 GB/s for a typical dual-channel DDR5 desktop. Small models (7 to 14 billion parameters at 4-bit) are usable; 70B models crawl."
url: https://exolabs.net/faq/can-i-run-an-llm-without-a-gpu/
updated: 2026-10-26
---

# Can I run an LLM without a GPU?

Yes, but large models will be slow. Tools such as llama.cpp run on ordinary CPUs, and speed is limited by system memory bandwidth, about 90 GB/s for a typical dual-channel DDR5 desktop. Small models (7 to 14 billion parameters at 4-bit) are usable; 70B models crawl.

Apple silicon Macs are the exception that makes this question less relevant: their GPU is built in and shares all of the system memory, at 307 GB/s on an M5 Pro and 1.2 TB/s on an M5 Ultra.

Mixture-of-experts models with few active parameters, such as gpt-oss-20b, run better on CPUs than dense models of the same size.

**Where exo fits:** On Linux, exo currently runs on CPU, with GPU support in development. On Macs it uses the built-in GPU through MLX.

Sources:
- [llama.cpp](https://github.com/ggml-org/llama.cpp)
- [Apple: Mac Studio tech specs](https://www.apple.com/mac-studio/specs/)
- [exo on GitHub (README)](https://github.com/exo-explore/exo)

Page: https://exolabs.net/faq/can-i-run-an-llm-without-a-gpu/ · Updated 2026-10-26 · Deployments: https://exolabs.net/#business (sales@exolabs.net)