Can I run it?
Can I run gemma 4 E4B it qat on GeForce RTX 3060 12GB?
Runs great
Runs great fully on your GeForce RTX 3060 12GB at UD-Q4_K_XL, 8K context, about 40–55 tok/s. Weights 3.93 GB plus 0.14 GB of KV cache — 4.41 GB of 10.9 GB usable. Up to 128K context still fits.
Best quantUD-Q4_K_XL
Working context8K
Max that fits128K
Speed40–55 tok/s
Weights3.93 GB
KV cache0.14 GB
Total4.41 GB
Usable10.9 GB
gemma 4 E4B it qat details · GeForce RTX 3060 12GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/gemma-4-E4B-it-qat-GGUF:UD-Q4_K_XL -c 8192 -ngl 42
Ollama
ollama run gemma
LM Studio
lms get unsloth/gemma-4-E4B-it-qat-GGUF # Then load quant UD-Q4_K_XL
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- UD-Q4_K_XL size is the real GGUF file size from Hugging Face.
- 0.5 GB is reserved because this GPU also drives a display, then 5% of the rest is left free.
- Speed is quoted at 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on GeForce RTX 3060 12GB? — Tight fit, UD-Q2_K_XL, 19–26 tok/s
- Can I run gemma 4 12b it on GeForce RTX 3060 12GB? — Tight fit, Q6_K, 15–21 tok/s
- Can I run Qwen3.5 9B on GeForce RTX 3060 12GB? — Tight fit, Q8_0, 20–28 tok/s
Updated 2026-10-17. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.