Written by Jakub Rusinowski · Last updated December 8, 2024
No — Llama 3.3 doesn't fit the NVIDIA GeForce RTX 4080 Super'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 5090 (32 GB).
| VRAM | 16 GB |
| Memory Bandwidth | 736 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context |
|---|---|---|---|
| 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 | — |
VRAM needed assumes a 4K-token context with an f16 KV cache; “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.
Every Llama 3.3 variant requires more VRAM than the NVIDIA GeForce RTX 4080 Super provides (16 GB).
NVIDIA GeForce RTX 5090 (32 GB VRAM).
Llama 3.3 needs ~26 GB but this GPU has 16 GB. Rent a A100 (40 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 4080 Super'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 5090 (32 GB).
The NVIDIA GeForce RTX 5090 (32 GB VRAM) is the cheapest upgrade that fits it.
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