# Can I run Gemma 3 12B on an RTX 4090? | What Can I Run AI?

> Yes. Gemma 3 12B at Q8_0 needs about 15.9 GB; RTX 4090 has 24.0 GB usable. Estimated tokens/sec and context headroom.

Source: https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-4090/

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**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](https://whatcanirunai.vercel.app/method/), 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](https://whatcanirunai.vercel.app/models/gemma-3-12b-it/) · [GeForce RTX 4090](https://whatcanirunai.vercel.app/hardware/rtx-4090/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/rtx-4090/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)

## Memory at each quant

| Quant    | Need vs 24.0 GB | Verdict       |
| -------- | --------------- | ------------- |
| Q4\_K\_M | 9.5 GB          | Q4Fits        |
| Q8\_0    | 15.9 GB         | Q8Fits        |
| FP16     | 29.0 GB         | FP16Won’t fit |

## 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](https://whatcanirunai.vercel.app/method/).

## 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](https://whatcanirunai.vercel.app/vram-calculator/) to explore longer chats.

## What to do instead

* See the [best GPU for this model family](https://whatcanirunai.vercel.app/best-gpu-for/gemma-3/) and the [gemma-3-12b-it model page](https://whatcanirunai.vercel.app/models/gemma-3-12b-it/).

## Other hardware for Gemma 3 12B

* [Gemma 3 12B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-3060-12gb/)Fits
* [Gemma 3 12B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-3070-ti/)Won’t fit
* [Gemma 3 12B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-3080-10gb/)Tight
* [Gemma 3 12B on an RTX 4060 Ti 16GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-4060-ti-16gb/)Tight
* [Gemma 3 12B on an RTX 4070 Ti Super](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-4070-ti-super/)Tight
* [Gemma 3 12B on an RTX 5070 Ti](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-5070-ti/)Tight

## Other models on an RTX 4090

* [Qwen3-32B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/qwen3-32b/rtx-4090/)Tight
* [Qwen3-30B-A3B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/qwen3-30b-a3b/rtx-4090/)Tight
* [Qwen3.8-27B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/qwen3.8-27b/rtx-4090/)Fits
* [Gemma 3 27B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/gemma-3-27b-it/rtx-4090/)Fits
* [Gemma 4 31B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-4090/)Tight
* [gpt-oss-20b on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-20b/rtx-4090/)Fits

## Quick answers

Can I run 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.

How much VRAM does Gemma 3 12B need?

About 9.5 GB at Q4\_K\_M, 15.9 GB at Q8\_0 and 29.0 GB at FP16, estimated for a \~4k context.

How fast is Gemma 3 12B on an RTX 4090?

Our estimate is 47–66 tokens per second at Q8\_0\. It is not a measured benchmark.

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