作者： Jakub Rusinowski · 最后更新： 2024年12月8日
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 5090 (32 GB).
| VRAM | 16 GB |
| Memory Bandwidth | 960 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 5080 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 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 5090 (32 GB).
The NVIDIA GeForce RTX 5090 (32 GB VRAM) is the cheapest upgrade that fits it.
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