How Much VRAM Do You Need to Run Llama 70B Locally? (2026)
Short answer: a 70-billion-parameter model needs roughly 24GB at the lowest quant and ~44–48GB for a good Q4 setup with usable context. Here's the real math, and the cheapest hardware that actually runs it.
The three things that use VRAM
Total memory isn't just the model file. It's:
- Weights — the model itself, and its size depends entirely on quantization (how compressed it is).
- KV cache — grows with your context length. Bigger context = more memory.
- Runtime buffer — a bit of overhead the backend needs.
So the honest formula is weights + KV cache + buffer. For a 70B model the weights dominate, and quant is the biggest lever you control.
VRAM for Llama 70B by quantization
| Quant | Weights (approx) | + context & buffer | Fits on… |
|---|---|---|---|
Q2_K | ~24 GB | ~26–28 GB | 1× 24GB card (tight) / 32GB+ |
Q4_K_M ⭐ | ~40 GB | ~44–48 GB | 2× 24GB (dual 3090) or 48GB card |
Q5_K_M | ~48 GB | ~52–56 GB | 48GB+ / 2× 24GB tight |
Q8_0 | ~73 GB | ~78–84 GB | 2× 48GB or 80GB card |
⭐ Q4_K_M is the sweet spot most people target — near-full quality at ~40% the memory of full precision.
What GPU do you actually need?
Matched to the quant you want to run:
Prices and availability change constantly — check current listings before buying. Links above are affiliate links that support the tool at no cost to you.
Can't fit it? Two cheaper options
1. Offload to system RAM. Backends like llama.cpp/Ollama can put some layers in regular RAM. It works on a smaller GPU, but it's much slower because system RAM bandwidth is a fraction of VRAM.
2. Rent a cloud GPU by the hour. If you only run 70B occasionally, renting an 80GB GPU for a few dollars/hour beats buying thousands in hardware. Providers like RunPod and Vast.ai are popular for this.
FAQ
Can I run a 70B model on 24GB of VRAM?
At Q2_K it just barely fits (or needs light offload) with reduced quality. Q4 does not fit on a single 24GB card without slow offload.
How much VRAM does Llama 70B need at Q4?
~40–43GB weights + context + buffer ≈ 44–48GB total. Dual 24GB or a 48GB card handles it.
Cheapest way to run 70B?
Two used RTX 3090s (48GB) to buy, or an hourly cloud GPU if you run it rarely.