Can I Run / Gemma 3 12B / on NVIDIA RTX 3060 12GB
Can I Run Gemma 3 12B on a NVIDIA RTX 3060 12GB?
Yes
Runs comfortably at Q6_K — minimal quality loss.
Model size
12.2B
GPU memory
12.0GB
Smallest quant
Q2_K
Best fit
Q6_K
11 quantizations fit your 12.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 11.1 GB | 12.6 GB | 9.7 GB | +0.9 GB |
| Q5_K_M | 9.7 GB | 11.2 GB | 8.4 GB | +2.3 GB |
| Q5_K_S | 9.4 GB | 10.9 GB | 8.2 GB | +2.6 GB |
| Q4_1 | 8.6 GB | 10.1 GB | 7.6 GB | +3.4 GB |
| Q4_K_M | 8.4 GB | 9.9 GB | 7.3 GB | +3.6 GB |
| Q4_K_S | 8.0 GB | 9.5 GB | 6.9 GB | +4.0 GB |
| Q4_0 | 7.9 GB | 9.4 GB | 6.9 GB | +4.1 GB |
| Q3_K_L | 6.4 GB | 7.9 GB | 6.5 GB | +5.6 GB |
| Q3_K_M | 6.1 GB | 7.6 GB | 6.0 GB | +5.9 GB |
| Q3_K_S | 5.7 GB | 7.2 GB | 5.5 GB | +6.3 GB |
| Q2_K | 5.0 GB | 6.5 GB | 4.8 GB | +7.0 GB |
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Full model details
Gemma 3 12B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 3060 12GB →
Top-ranked open-source models that fit in 12.0GB.
FAQ
Can the NVIDIA RTX 3060 12GB run Gemma 3 12B?
Yes. The NVIDIA RTX 3060 12GB's 12.0GB of VRAM is enough to run Gemma 3 12B at Q6_K quantization (11.1GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 12.0GB. It uses about 11.1GB of memory and 12.6GB 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.