Home / Can I run it? / Gemma 3 12B / Gemma 3 12B on an RTX 4090

Yes. Gemma 3 12B at Q8_0 needs about 15.9 GB, and the GeForce RTX 4090 has 24.0 GB usable at a ~4k context.

Can I run Gemma 3 12B on an RTX 4090?

Gemma 3 12B at Q8_0 needs about 15.9 GB, and the GeForce RTX 4090 has 24.0 GB usable. That figure is 24 GB of VRAM on the spec sheet, of which 24.0 GB is usable for weights and cache, at 1008 GB/s memory bandwidth. Google’s mid-small Gemma 3, sized for 12–16 GB cards that want more than a 4B or 8B. These are estimates from our formula, not measured benchmarks.

Quant that fits

Q8_0 Fits with headroom

Memory needed

15.9 GB at Q8_0, ~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

47–66 estimate

gemma-3-12b-it · GeForce RTX 4090 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

Estimate: 47–66 tokens/sec at Q8_0. This is a bandwidth-derived range, not a bench. Efficiency is a 60–85% GPU band from How we calculate.

Context headroom

We do not have a published KV config for this model, so the memory need is the ~4k-context estimate only. Use the VRAM calculator to explore longer chats.

What to do instead

• See the best GPU for this model family and the gemma-3-12b-it model page.

Other hardware for Gemma 3 12B

• Gemma 3 12B on an RTX 3060 12GBFits
• Gemma 3 12B on an RTX 3070 TiWon’t fit
• Gemma 3 12B on an RTX 3080Tight
• Gemma 3 12B on an RTX 4060 Ti 16GBTight
• Gemma 3 12B on an RTX 4070 Ti SuperTight
• Gemma 3 12B on an RTX 5070 TiTight

Other models on an RTX 4090

• Qwen3-32B on an RTX 4090Tight
• Qwen3-30B-A3B on an RTX 4090Tight
• Qwen3.8-27B on an RTX 4090Fits
• Gemma 3 27B on an RTX 4090Fits
• Gemma 4 31B on an RTX 4090Tight
• gpt-oss-20b on an RTX 4090Fits