Can I Run Gemma 3 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?

Written by Jakub Rusinowski · Last updated March 12, 2025

Yes, but it is tight

Yes, but it is tight — Gemma 3 12B Instruct at Q4_K_M needs about 11.1 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM), leaving only ~0.9 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: Q4_K_M · Estimated speed: ~28.7 tok/s

RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM) — what it gives a model

Usable memory for models12 GB
Memory bandwidth360 GB/s
Form factorDesktop
Operating systemWindows or Linux
Memory upgradeableYes

Gemma 3 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM): memory by quantization

QuantMemory neededFits 12 GB?Max contextEst. speedDownload
F1627.9 GB✗ No24 GB
Q8_016.6 GB✗ No12.8 GB
Q6_K13.7 GB✗ No9.8 GB
Q5_K_M12.4 GB✗ No8.5 GB
Q4_K_M11.1 GB✓ Yes8K~28.7 tok/s7.2 GB
Q3_K_M9 GB✓ Yes8K~37.2 tok/s5.1 GB
Q2_K7.8 GB✓ Yes16K~44.3 tok/s3.9 GB

Which Gemma 3 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Gemma 3 27B Instruct25.4 GB✗ Too large
Gemma 3 12B Instruct11.1 GB✓ Fits~28.7 tok/s
Gemma 3 4B Instruct4.4 GB✓ Fits~75.2 tok/s
Gemma 3 1B Instruct2 GB✓ Fits~178.6 tok/s

What to watch out for

RTX 3060 12 GB desktop limitations

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

FAQ

Can I run Gemma 3 on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?

Yes, but it is tight — Gemma 3 12B Instruct at Q4_K_M needs about 11.1 GB of the 12 GB usable on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM), leaving only ~0.9 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 3 should I use on RTX 3060 12 GB Desktop (12 GB VRAM, 32 GB RAM)?

Q4_K_M — it needs about 11.1 GB of the 12 GB available, downloads as roughly 7.2 GB, and runs at an estimated 28.7 tokens/sec with up to 8K of context.

What limits Gemma 3 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 GPUs

What This Model Is Good At

Model & Tools

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