# Can I run Gemma 3 4B on an Arc B580? | What Can I Run AI?

> Yes, but it is tight. Gemma 3 4B at FP16 needs about 10.9 GB; Arc B580 has 12.0 GB usable. Estimated tokens/sec and context headroom.

Source: https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/arc-b580/

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**Yes, but it is tight.** Gemma 3 4B at FP16 needs about 10.9 GB, and the Intel Arc B580 has 12.0 GB usable at a \~4k context.

# Can I run Gemma 3 4B on an Arc B580?

Gemma 3 4B at FP16 needs about 10.9 GB, and the Intel Arc B580 has 12.0 GB usable. That figure is 12 GB of VRAM on the spec sheet, of which 12.0 GB is usable for weights and cache, at 456 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, short context only

Memory needed

10.9 GB at FP16, \~4k context

Usable VRAM

12.0 GB of 12 GB VRAM

Est. tokens/sec

32–45 estimate

[gemma-3-4b-it](https://whatcanirunai.vercel.app/models/gemma-3-4b-it/) · [Intel Arc B580](https://whatcanirunai.vercel.app/hardware/arc-b580/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/arc-b580/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)

## Memory at each quant

| Quant    | Need vs 12.0 GB | Verdict   |
| -------- | --------------- | --------- |
| Q4\_K\_M | 4.0 GB          | Q4Fits    |
| Q8\_0    | 6.3 GB          | Q8Fits    |
| FP16     | 10.9 GB         | FP16Tight |

## Estimated tokens per second

Estimate: **32–45 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

* Run [Llama 3.2 3B](https://whatcanirunai.vercel.app/can-i-run/llama-3.2-3b-instruct/arc-b580/) instead (3.2 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
* Keep context short, close other GPU work, and avoid a higher quant. The [VRAM calculator](https://whatcanirunai.vercel.app/vram-calculator/) shows how the KV cache grows.
* 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 RTX 4090](https://whatcanirunai.vercel.app/can-i-run/gemma-3-4b-it/rtx-4090/)Fits
* [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 Arc B580

* [Qwen3-32B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/qwen3-32b/arc-b580/)Won’t fit
* [Qwen3-30B-A3B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/qwen3-30b-a3b/arc-b580/)Won’t fit
* [Qwen3.8-27B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/qwen3.8-27b/arc-b580/)Won’t fit
* [Gemma 3 27B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/gemma-3-27b-it/arc-b580/)Won’t fit
* [Gemma 4 31B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/arc-b580/)Won’t fit
* [gpt-oss-20b on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-20b/arc-b580/)Won’t fit

## Quick answers

Can I run Gemma 3 4B on an Arc B580?

Yes, but it is tight. Gemma 3 4B at FP16 needs about 10.9 GB, and the Intel Arc B580 has 12.0 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 Arc B580?

Our estimate is 32–45 tokens per second at FP16\. It is not a measured benchmark.

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