Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
No — Llama 3.3 doesn't fit the NVIDIA GeForce RTX 5080's 16 GB; you're short by ~9.2 GB even at Q2_K. The cheapest card that runs it is the NVIDIA GeForce RTX 4090 (24 GB).
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| VRAM | 16 GB |
| Memory Bandwidth | 960 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 142.1 GB | ✗ No | — | — |
| Q8_0 | 76.5 GB | ✗ No | — | — |
| Q6_K | 59.5 GB | ✗ No | — | — |
| Q5_K_M | 51.8 GB | ✗ No | — | — |
| Q4_K_M | 44.4 GB | ✗ No | — | — |
| Q3_K_M | 32 GB | ✗ No | — | — |
| Q2_K | 25.2 GB | ✗ No | — | — |
Assumes a 4K-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 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q2_K_XS (Tight) on the NVIDIA GeForce RTX 5080: 8K 23.7 GB ✗ · 32K 31.7 GB ✗ · 128K 64 GB ✗. Past 8K it no longer fits 16 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.
Every Llama 3.3 variant requires more VRAM than the NVIDIA GeForce RTX 5080 provides (16 GB).
NVIDIA GeForce RTX 4090 (24 GB VRAM).
Llama 3.3 needs ~20 GB but this GPU has 16 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
No — Llama 3.3 doesn't fit the NVIDIA GeForce RTX 5080's 16 GB; you're short by ~9.2 GB even at Q2_K. The cheapest card that runs it is the NVIDIA GeForce RTX 4090 (24 GB).
The NVIDIA GeForce RTX 4090 (24 GB VRAM) is the cheapest upgrade that fits it.
← Can I Run It? | Llama 3.3 Model Page | NVIDIA GeForce RTX 5080 GPU Page | Check Your Hardware