# Llama 3.1 8B: RAM and VRAM requirements

> Llama 3.1 8B is a 8B llama model. At Q4_K_M it needs about **6.4 GB** to run and fits **32 of 39** tracked devices. Minimum to run: Nvidia GeForce RTX 3060 (12GB).

Last validated: 2026-06-15. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 4.92 GB | ~6.4 GB |
| Q8_0 | 8.54 GB | ~10 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
- **Generic Android Phone (8GB RAM)** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): Yes, it runs
- **Nvidia GeForce RTX 4080 (16GB)** (16 GB): Yes, it runs — room for Q8_0
- **Google Pixel 10 Pro** (16 GB): Yes, it runs — room for Q8_0
- **Nvidia GeForce RTX 4090 (24GB)** (24 GB): Yes, it runs — room for FP16
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs — room for FP16
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs — room for FP16

Full table of all 39 devices: https://localmodel.run/model/llama-3.1-8b

## How to run
Quickest path: `ollama run llama3.1:8b`. On Mac, LM Studio (ships MLX) is fastest; on Linux, Ollama for chat or vLLM to serve; on Windows, LM Studio or Ollama.

## Details
- Parameters: 8B
- Default context: 128k tokens
- License: Llama 3.1 Community (commercial use: conditional)
- Released: 2024-07
- HuggingFace: 6,599,474 downloads/mo, 6079 likes

## FAQ
### How much VRAM or RAM does Llama 3.1 8B need?
About 6.4 GB at Q4_K_M (weights 4.92 GB + KV cache + overhead) at a 4k context. Budget ~10 GB for Q8_0.
### Can Llama 3.1 8B run on a laptop?
Yes. Llama 3.1 8B fits on a 16 GB laptop or Mac at Q4_K_M, and runs on Apple Silicon or a 12 GB+ GPU comfortably.
### Can I use Llama 3.1 8B commercially?
Conditionally: Llama 3.1 Community License: free under 700M MAU..

Sources: https://ollama.com/library/llama3.1, https://ollama.com/library/llama3.1/tags, https://huggingface.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF, https://lmarena.ai/leaderboard
More: https://localmodel.run/model/llama-3.1-8b