Can I Run Llama 3.2 11B Vision on a NVIDIA RTX 2080?
Runs at Q4_K_M — good quality with reasonable headroom.
1 quant fit your 8.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_MBEST | 7.7 GB | 9.2 GB | 6.7 GB | +0.3 GB |
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FAQ
Can the NVIDIA RTX 2080 run Llama 3.2 11B Vision?
Yes. The NVIDIA RTX 2080's 8.0GB of VRAM is enough to run Llama 3.2 11B Vision at Q4_K_M quantization (7.7GB required).
What's the best quantization to use?
Q4_K_M is the highest-precision quantization that fits in your 8.0GB. It uses about 7.7GB of memory and 9.2GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.