Can I Run Llama 3.2 Vision on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Superseded model. Llama 3.2 Vision has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point.
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Written by Jakub Rusinowski · Last updated September 25, 2024
Yes
Yes — Llama 3.2 Vision 11B at Q6_K needs about 10.8 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM) (~1.2 GB spare), at ~27.1 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~27.1 tok/s
RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM) — what it gives a model
| Usable memory for models | 12 GB |
| Memory bandwidth | 360 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
Llama 3.2 Vision on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM): memory by quantization
| Quant | Memory needed | Fits 12 GB? | Max context | Est. speed | Download |
|---|
| F16 | 23.3 GB | ✗ No | — | — | 21.2 GB |
| Q8_0 | 13.4 GB | ✗ No | — | — | 11.3 GB |
| Q6_K | 10.8 GB | ✓ Yes | 8K | ~27.1 tok/s | 8.7 GB |
| Q5_K_M | 9.7 GB | ✓ Yes | 16K | ~30.7 tok/s | 7.5 GB |
| Q4_K_M | 8.5 GB | ✓ Yes | 16K | ~35.2 tok/s | 6.4 GB |
| Q3_K_M | 6.7 GB | ✓ Yes | 32K | ~46.6 tok/s | 4.5 GB |
| Q2_K | 5.6 GB | ✓ Yes | 32K | ~56.7 tok/s | 3.5 GB |
Which Llama 3.2 Vision sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Llama 3.2 Vision 90B | 57.8 GB | ✗ Too large | — |
| Llama 3.2 Vision 11B | 8.5 GB | ✓ Fits | ~35.2 tok/s |
What to watch out for
- Only ~1.2 GB of headroom at Q6_K: a longer context or a second application can push this into swapping.
- 1 larger variant of Llama 3.2 Vision does not fit and would need CPU offload or different hardware.
RTX 3060 12 GB desktop limitations
- The budget entry point to local AI: 12 GB runs 7–14B models well and nothing larger without offload.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 12 GB of VRAM on the NVIDIA GeForce RTX 3060 (12GB) at 360 GB/s.
- 32 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Llama 3.2 Vision on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Yes — Llama 3.2 Vision 11B at Q6_K needs about 10.8 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM) (~1.2 GB spare), at ~27.1 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Llama 3.2 Vision should I use on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Q6_K — it needs about 10.8 GB of the 12 GB available, downloads as roughly 8.7 GB, and runs at an estimated 27.1 tokens/sec with up to 8K of context.
What limits Llama 3.2 Vision on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
Llama 3.2 Vision on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Llama 3.2 Vision model page | Check your hardware