Can an NVIDIA GeForce RTX 4090 run Llama-3.1-70B-Instruct?
Yes, with CPU offload. Llama-3.1-70B-Instruct needs 45.8GB at Q4_K_M with llama.cpp and 8K context; the NVIDIA GeForce RTX 4090 has 24GB of VRAM (23.5GB usable), so part of the model spills to system RAM — it loads, but expect the usable speed tier.
NVIDIA GeForce RTX 4090 · Llama-3.1-70B-Instruct · Q4_K_M
⚠️ Tight — grade C
UsablebetaCPU offload — speed varies heavily with layer split
weights 42.5 GBKV cache 2.68 GBoverhead 0.62 GBpool 23.5 GBneeds 45.8 GB — spills to system RAM
assumes llama.cpp · batch 1 · 8K context · fp16 KV cache · 64GB system RAM (CPU offload)
$1,599 MSRP · as of 2026-07-08
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Every quant, graded
NVIDIA GeForce RTX 4090 × Llama-3.1-70B-Instruct, llama.cpp, 8K context.
| Quant | File size | Fit | Speed tier |
|---|---|---|---|
| Q8_0 | 75.0 GB | Won't fit | |
| Q6_K | 57.9 GB | Tight · C | painful · offload · beta |
| Q5_K_M | 50.0 GB | Tight · C | painful · offload · beta |
| Q4_K_M | 42.5 GB | Tight · C | usable · offload · beta |
Llama-3.1-70B-Instruct on similar hardware
More models on the NVIDIA GeForce RTX 4090
Verdict computed from published specs and measured GGUF file sizes — see how the math works.