📍 Part of the Local LLMs in 2026 guide
❌ No — not enough VRAM without CPU offloading
Llama 3.1 70B needs 40 GB VRAM at Q4. The RTX 4090 24GB has 24 GB.
Llama 3.1 70B needs 40 GB VRAM at Q4. The RTX 4090 24GB has 24 GB.
● Llama 3.1 70B (Meta) is a 70B parameter model used for Near-GPT-4 quality for complex tasks. Frontier-class open model, best for demanding use cases.
VRAM Requirements
| Quantization | VRAM Needed | RTX 4090 24GB |
|---|---|---|
| Q4_K_M (recommended) | 40 GB | ❌ |
| Q8_0 (high quality) | 72 GB | ❌ |
Why It Won’t Fit
Llama 3.1 70B needs 40 GB VRAM at Q4 quantization, but the RTX 4090 24GB only has 24 GB. You’re 16 GB short.
Options: You can run it with CPU offloading (expect ~10 tok/s — very slow), or upgrade to a GPU with 40+ GB VRAM.
About the RTX 4090 24GB
Pros: Fastest consumer GPU, excellent for real-time inference
Cons: Expensive, still only 24GB limits 70B models
Price: ~$1,800 — Check current price on Amazon →