# Can I run Gemma 4 31B on an Arc B580? | What Can I Run AI?

> No. Gemma 4 31B needs about 22.8 GB at Q4_K_M, and Arc B580 has 12.0 GB usable. What to run instead.

Source: https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/arc-b580/

[Home](https://whatcanirunai.vercel.app/) / [Can I run it?](https://whatcanirunai.vercel.app/can-i-run/) / [Gemma 4 31B](https://whatcanirunai.vercel.app/models/gemma-4-31b-it/) / Gemma 4 31B on an Arc B580

**No.** Gemma 4 31B at Q4\_K\_M needs about 22.8 GB, and the Intel Arc B580 has 12.0 GB usable at a \~4k context.

# Can I run Gemma 4 31B on an Arc B580?

Gemma 4 31B at Q4\_K\_M needs about 22.8 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 dense Gemma 4 31B. Close in memory to Qwen3-32B, with a different training mix. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

None of Q4, Q8 or FP16 needs 22.8 GB

Memory needed

22.8 GB at Q4\_K\_M, \~4k context

Usable VRAM

12.0 GB of 12 GB VRAM

Est. tokens/sec

n/a does not fit

[Gemma 4 31B](https://whatcanirunai.vercel.app/models/gemma-4-31b-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 | 22.8 GB         | Q4Won’t fit   |
| Q8\_0    | 39.2 GB         | Q8Won’t fit   |
| FP16     | 72.9 GB         | FP16Won’t fit |

## Estimated tokens per second

No speed estimate: Gemma 4 31B does not fit in the 12.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.

## 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 [R1 Distill 14B](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/arc-b580/) instead (11.3 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
* To hold Gemma 4 31B at Q4, you need about 22.8 GB. The [GeForce RTX 3090](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3090/) has 24.0 GB usable ($1499 list price).
* CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
* See the [best GPU for this model family](https://whatcanirunai.vercel.app/best-gpu-for/gemma-4/) and the [Gemma 4 31B model page](https://whatcanirunai.vercel.app/models/gemma-4-31b-it/).

## Other hardware for Gemma 4 31B

* [Gemma 4 31B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3060-12gb/)Won’t fit
* [Gemma 4 31B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3070-ti/)Won’t fit
* [Gemma 4 31B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3080-10gb/)Won’t fit
* [Gemma 4 31B on an RTX 3090](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3090/)Tight
* [Gemma 4 31B on an RTX 4060 Ti 16GB](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-4060-ti-16gb/)Won’t fit
* [Gemma 4 31B on an RTX 4070 Ti Super](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-4070-ti-super/)Won’t fit

## 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
* [gpt-oss-20b on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-20b/arc-b580/)Won’t fit
* [Mistral Small 24B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/mistral-small-3.2-24b-instruct-2506/arc-b580/)Won’t fit

## Quick answers

Can I run Gemma 4 31B on an Arc B580?

No. Gemma 4 31B at Q4\_K\_M needs about 22.8 GB, and the Intel Arc B580 has 12.0 GB usable.

How much VRAM does Gemma 4 31B need?

About 22.8 GB at Q4\_K\_M, 39.2 GB at Q8\_0 and 72.9 GB at FP16, estimated for a \~4k context.

How fast is Gemma 4 31B on an Arc B580?

We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.

---
Agent guide: https://whatcanirunai.vercel.app/llms.txt · JSON API: https://whatcanirunai.vercel.app/developers/