# Can I run Gemma 3 4B on an RTX 4090? | What Can I Run AI?

> Yes. Gemma 3 4B at FP16 needs about 10.9 GB; RTX 4090 has 24.0 GB usable. Estimated tokens/sec and context headroom.

Source: https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/rtx-4090/

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**Yes.** Gemma 3 4B at FP16 needs about 10.9 GB, and the GeForce RTX 4090 has 24.0 GB usable at a \~4k context.

# Can I run Gemma 3 4B on an RTX 4090?

Gemma 3 4B at FP16 needs about 10.9 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 small Gemma 3 instruct model, a good low-VRAM option with a different flavor from Llama 3.2 3B. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

FP16 Fits with headroom

Memory needed

10.9 GB at FP16, \~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

70–100 estimate

[gemma-3-4b-it](https://whatcanirunai.vercel.app/models/gemma-3-4b-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 | 4.0 GB          | Q4Fits   |
| Q8\_0    | 6.3 GB          | Q8Fits   |
| FP16     | 10.9 GB         | FP16Fits |

## Estimated tokens per second

Estimate: **70–100 tokens/sec** at FP16\. 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-3-4b-it model page](https://whatcanirunai.vercel.app/models/gemma-3-4b-it/).

## Other hardware for Gemma 3 4B

* [Gemma 3 4B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/rtx-3060-12gb/)Tight
* [Gemma 3 4B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/rtx-3070-ti/)Fits
* [Gemma 3 4B on an RTX 4060 Ti 16GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/rtx-4060-ti-16gb/)Fits
* [Gemma 3 4B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/arc-b580/)Tight
* [Gemma 3 4B on a Mac mini 16GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/mac-mini-m6-16/)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 4B on an RTX 4090?

Yes. Gemma 3 4B at FP16 needs about 10.9 GB, and the GeForce RTX 4090 has 24.0 GB usable.

How much VRAM does Gemma 3 4B need?

About 4.0 GB at Q4\_K\_M, 6.3 GB at Q8\_0 and 10.9 GB at FP16, estimated for a \~4k context.

How fast is Gemma 3 4B on an RTX 4090?

Our estimate is 70–100 tokens per second at FP16\. It is not a measured benchmark.

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