Can I Run Gemma 2 Family on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Written by Jakub Rusinowski · Last updated June 27, 2024
Yes, but it is tight
Yes, but it is tight — Gemma 2 9B IT at Q6_K needs about 11 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM), leaving only ~1 GB before the runtime starts swapping. Expect ~28.7 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~28.7 tok/s
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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 |
Gemma 2 Family 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 | 21.6 GB | ✗ No | — | — | 18 GB |
| Q8_0 | 13.2 GB | ✗ No | — | — | 9.6 GB |
| Q6_K | 11 GB | ✓ Yes | 8K | ~28.7 tok/s | 7.4 GB |
| Q5_K_M | 10 GB | ✓ Yes | 8K | ~32.2 tok/s | 6.4 GB |
| Q4_K_M | 9.1 GB | ✓ Yes | 8K | ~36.2 tok/s | 5.4 GB |
| Q3_K_M | 7.5 GB | ✓ Yes | 8K | ~46.1 tok/s | 3.8 GB |
| Q2_K | 6.6 GB | ✓ Yes | 8K | ~54.3 tok/s | 3 GB |
What to watch out for
- Only ~1 GB of headroom at Q6_K: a longer context or a second application can push this into swapping.
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 Gemma 2 Family on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Yes, but it is tight — Gemma 2 9B IT at Q6_K needs about 11 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM), leaving only ~1 GB before the runtime starts swapping. Expect ~28.7 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Gemma 2 Family should I use on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?
Q6_K — it needs about 11 GB of the 12 GB available, downloads as roughly 7.4 GB, and runs at an estimated 28.7 tokens/sec with up to 8K of context.
What limits Gemma 2 Family 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)
- Gemma 3 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
- Gemma 3n on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
- Gemma 4 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
- GLM-4.7 / GLM-Z1 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
- GLM-5 / GLM-5.1 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)
Gemma 2 Family on GPUs
- Gemma 2 Family on NVIDIA GeForce RTX 5070
- Gemma 2 Family on NVIDIA GeForce RTX 5060 Ti 8GB
- Gemma 2 Family on NVIDIA GeForce RTX 5060
- Gemma 2 Family on NVIDIA GeForce RTX 4070 Ti
What This Model Is Good At
Model & Tools
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