Can I Run gemma 4 12B it on a NVIDIA RTX 5060?
Runs at Q4_K_S — good quality with reasonable headroom.
6 quantizations fit your 8.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_SBEST | 7.9 GB | 9.4 GB | 6.8 GB | +0.1 GB |
| Q4_0 | 7.8 GB | 9.3 GB | 6.7 GB | +0.3 GB |
| Q3_K_L | 6.3 GB | 7.8 GB | 6.7 GB | +1.7 GB |
| Q3_K_M | 6.0 GB | 7.5 GB | 5.7 GB | +2.0 GB |
| Q3_K_S | 5.6 GB | 7.1 GB | 5.1 GB | +2.4 GB |
| Q2_K | 5.0 GB | 6.5 GB | 5.1 GB | +3.0 GB |
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Top-ranked open-source models that fit in 8.0GB.
FAQ
Can the NVIDIA RTX 5060 run gemma 4 12B it?
Yes. The NVIDIA RTX 5060's 8.0GB of VRAM is enough to run gemma 4 12B it at Q4_K_S quantization (7.9GB required).
What's the best quantization to use?
Q4_K_S is the highest-precision quantization that fits in your 8.0GB. It uses about 7.9GB of memory and 9.4GB 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.