Can I Run Llama 3.3 on NVIDIA GeForce RTX 5090?

Written by Jakub Rusinowski · Last updated September 29, 2026

Yes, comfortably — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), leaving ~8.3 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~61 tok/s (est.).

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NVIDIA GeForce RTX 5090 32GB
32 GB VRAM · 575 W board power
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NVIDIA GeForce RTX 5090 Specs

VRAM32 GB
Memory Bandwidth1792 GB/s

Llama 3.3 70B Instruct on the NVIDIA GeForce RTX 5090: VRAM by quantization

QuantVRAM neededFits 32 GB?Max contextWhole PC
F16143.5 GB✗ No——
Q8_077.9 GB✗ No——
Q6_K60.9 GB✗ No——
Q5_K_M53.1 GB✗ No——
Q4_K_M45.7 GB✗ No——
Q3_K_M33.3 GB✗ No——
Q2_K26.5 GB✓ Yes16K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 32 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Superseded model. Llama 3.3 has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point. Llama 4 needs at least 68.2 GB at Q4_K_M with an 8K context, so it does not fit the NVIDIA GeForce RTX 5090.

Context costs VRAM too. At Q2_K_XS (Tight) on the NVIDIA GeForce RTX 5090: 8K 23.7 GB · 32K 31.7 GB · 128K 64 GB ✗. Past 128K it no longer fits 32 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

No compatible GPU? Llama 3.3 70B Instruct on 256 GB of system RAM, CPU only: runs, but too slowly to be worth it.

Llama 3.3 Sizes That Fit the NVIDIA GeForce RTX 5090 (at 8K context)

Llama 3.3 70B InstructQ2_K_XS (Tight) · 23.7 GB at 8K context · ~61 tok/s (est.)
Buy vs. rent Llama 3.3
Buy the GPU
~$1,999
NVIDIA GeForce RTX 5090 · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$1,999) beats renting at $0.34/hr after about 8.2 years.

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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Will Llama 3.3 run on the NVIDIA GeForce RTX 5090?

Yes, comfortably — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), leaving ~8.3 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~61 tok/s (est.).

Which Llama 3.3 variant fits best on the NVIDIA GeForce RTX 5090?

Llama 3.3 70B Instruct at Q2_K_XS (Tight) quantization needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), estimated ~61 tokens/sec.

Llama 3.3 on Other GPUs

Popular Models on the NVIDIA GeForce RTX 5090

VRAM Tier

Troubleshooting

Buying Guide

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