Can an NVIDIA GeForce RTX 5090 run Llama-3.1-8B-Instruct?
Yes. Llama-3.1-8B-Instruct needs 10.1GB at Q8_0 with llama.cpp and 8K context; the NVIDIA GeForce RTX 5090 has 32GB of VRAM (31.5GB usable) — grade A+, with decode speed in the interactive tier.
NVIDIA GeForce RTX 5090 · Llama-3.1-8B-Instruct · Q8_0
✅ Fits — grade A+
Interactive
weights 8.54 GBKV cache 1.07 GBoverhead 0.48 GBpool 31.5 GBneeds 10.1 GB
assumes llama.cpp · batch 1 · 8K context · fp16 KV cache
$1,999 MSRP · as of 2026-07-08
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Every quant, graded
NVIDIA GeForce RTX 5090 × Llama-3.1-8B-Instruct, llama.cpp, 8K context.
| Quant | File size | Fit | Speed tier |
|---|---|---|---|
| Q8_0 | 8.5 GB | Fits · A+ | interactive |
| Q6_K | 6.6 GB | Fits · A+ | interactive |
| Q5_K_M | 5.7 GB | Fits · A+ | interactive |
| Q4_K_M | 4.9 GB | Fits · A+ | interactive |
Llama-3.1-8B-Instruct on similar hardware
More models on the NVIDIA GeForce RTX 5090
Verdict computed from published specs and measured GGUF file sizes — see how the math works.