# Can I run Qwen3-14B on an RTX 3060 12GB? | What Can I Run AI

> Yes, but it is tight. Qwen3-14B at Q4_K_M needs about 11.3 GB; RTX 3060 12GB has 12.0 GB usable. Estimated tokens/sec and context headroom.

Source: https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3060-12gb/

[Home](https://whatcanirunai.vercel.app/) / [Can I run it?](https://whatcanirunai.vercel.app/can-i-run/) / [Qwen3-14B](https://whatcanirunai.vercel.app/models/qwen3-14b/) / Qwen3-14B on an RTX 3060 12GB

**Yes, but it is tight.** Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3060 12GB has 12.0 GB usable at a \~4k context.

# Can I run Qwen3-14B on an RTX 3060 12GB?

Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3060 12GB 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 360 GB/s memory bandwidth. Alibaba’s 14B Qwen3\. It sits in the sweet spot for 12–16 GB cards that want more quality than an 8B. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

Q4\_K\_M Fits, short context only

Memory needed

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

Usable VRAM

12.0 GB of 12 GB VRAM

Est. tokens/sec

24–34 estimate

[Qwen3-14B](https://whatcanirunai.vercel.app/models/qwen3-14b/) · [GeForce RTX 3060 12GB](https://whatcanirunai.vercel.app/hardware/rtx-3060-12gb/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3060-12gb/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)

## Memory at each quant

| Quant    | Need vs 12.0 GB | Verdict       |
| -------- | --------------- | ------------- |
| Q4\_K\_M | 11.3 GB         | Q4Tight       |
| Q8\_0    | 19.0 GB         | Q8Won’t fit   |
| FP16     | 35.0 GB         | FP16Won’t fit |

## Estimated tokens per second

Estimate: **24–34 tokens/sec** at Q4\_K\_M. 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

At Q4\_K\_M, this machine has headroom out to about **8k tokens** under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.

__Context headroom for Qwen3-14B on an RTX 3060 12GB at Q4\_K\_M__
| Context | KV cache (FP16) | Total at Q4\_K\_M | Verdict   |
| ------- | --------------- | ----------------- | --------- |
| 4k      | 0.7 GB          | 11.3 GB           | Tight     |
| 8k      | 1.3 GB          | 12.0 GB           | Tight     |
| 16k     | 2.7 GB          | 13.3 GB           | Won’t fit |
| 32k     | 5.4 GB          | 16.0 GB           | Won’t fit |
| 64k     | 10.7 GB         | 21.4 GB           | Won’t fit |
| 128k    | 21.5 GB         | 32.1 GB           | Won’t fit |

From the model’s config. Try other sizes in the [VRAM calculator](https://whatcanirunai.vercel.app/vram-calculator/) or see the [context length guide](https://whatcanirunai.vercel.app/context-length/).

## What to do instead

* Run [Phi-4](https://whatcanirunai.vercel.app/can-i-run/phi-4/rtx-3060-12gb/) instead (11.2 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
* Q8\_0 needs 19.0 GB and does not fit here. The [Radeon RX 7900 XT](https://whatcanirunai.vercel.app/hardware/rx-7900-xt/) has 20.0 GB usable, enough for Q8.
* See the [best GPU for this model family](https://whatcanirunai.vercel.app/best-gpu-for/qwen3/) and the [Qwen3-14B model page](https://whatcanirunai.vercel.app/models/qwen3-14b/).

## Other hardware for Qwen3-14B

* [Qwen3-14B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3070-ti/)Won’t fit
* [Qwen3-14B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3080-10gb/)Won’t fit
* [Qwen3-14B on an RTX 4060 Ti 16GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4060-ti-16gb/)Fits
* [Qwen3-14B on an RTX 4070 Ti Super](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4070-ti-super/)Fits
* [Qwen3-14B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4090/)Fits
* [Qwen3-14B on an RTX 5070 Ti](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-5070-ti/)Fits

## Other models on an RTX 3060 12GB

* [Qwen3-32B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-32b/rtx-3060-12gb/)Won’t fit
* [Qwen3-30B-A3B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-30b-a3b/rtx-3060-12gb/)Won’t fit
* [Qwen3.8-27B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/qwen3.8-27b/rtx-3060-12gb/)Won’t fit
* [Gemma 3 27B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/gemma-3-27b-it/rtx-3060-12gb/)Won’t fit
* [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
* [gpt-oss-20b on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-20b/rtx-3060-12gb/)Won’t fit

## Quick answers

Can I run Qwen3-14B on an RTX 3060 12GB?

Yes, but it is tight. Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3060 12GB has 12.0 GB usable.

How much VRAM does Qwen3-14B need?

About 11.3 GB at Q4\_K\_M, 19.0 GB at Q8\_0 and 35.0 GB at FP16, estimated for a \~4k context.

How fast is Qwen3-14B on an RTX 3060 12GB?

Our estimate is 24–34 tokens per second at Q4\_K\_M. It is not a measured benchmark.

What context length can I use?

At Q4\_K\_M, our KV estimate supports up to about 8k tokens before the cache pushes the total over usable memory.

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