# Can I run R1 Distill 14B on an RTX 4090? | What Can I Run AI

> Yes. R1 Distill 14B at Q8_0 needs about 19.0 GB; RTX 4090 has 24.0 GB usable. Estimated tokens/sec and context headroom.

Source: https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/rtx-4090/

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**Yes.** R1 Distill 14B at Q8\_0 needs about 19.0 GB, and the GeForce RTX 4090 has 24.0 GB usable at a \~4k context.

# Can I run R1 Distill 14B on an RTX 4090?

R1 Distill 14B at Q8\_0 needs about 19.0 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. A 14B DeepSeek-R1 distill on Qwen. Same memory class as other 14B dense models, with reasoning-tuned weights. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

Q8\_0 Fits with headroom

Memory needed

19.0 GB at Q8\_0, \~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

39–55 estimate

[DeepSeek-R1-Distill-Qwen-14B](https://whatcanirunai.vercel.app/models/deepseek-r1-distill-qwen-14b/) · [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 | 11.3 GB         | Q4Fits        |
| Q8\_0    | 19.0 GB         | Q8Fits        |
| FP16     | 35.0 GB         | FP16Won’t fit |

## Estimated tokens per second

Estimate: **39–55 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

At Q8\_0, this machine has headroom out to about **16k tokens** under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.

__Context headroom for R1 Distill 14B on an RTX 4090 at Q8\_0__
| Context | KV cache (FP16) | Total at Q8\_0 | Verdict   |
| ------- | --------------- | -------------- | --------- |
| 4k      | 0.8 GB          | 19.0 GB        | Fits      |
| 8k      | 1.6 GB          | 19.9 GB        | Fits      |
| 16k     | 3.2 GB          | 21.5 GB        | Fits      |
| 32k     | 6.4 GB          | 24.7 GB        | Won’t fit |
| 64k     | 12.9 GB         | 31.1 GB        | Won’t fit |
| 128k    | 25.8 GB         | 44.0 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

* See the [best GPU for this model family](https://whatcanirunai.vercel.app/best-gpu-for/deepseek-r1/) and the [DeepSeek-R1-Distill-Qwen-14B model page](https://whatcanirunai.vercel.app/models/deepseek-r1-distill-qwen-14b/).

## Other hardware for R1 Distill 14B

* [R1 Distill 14B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/rtx-3060-12gb/)Tight
* [R1 Distill 14B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/rtx-3070-ti/)Won’t fit
* [R1 Distill 14B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/arc-b580/)Tight
* [R1 Distill 14B on a Mac mini 16GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-14b/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 R1 Distill 14B on an RTX 4090?

Yes. R1 Distill 14B at Q8\_0 needs about 19.0 GB, and the GeForce RTX 4090 has 24.0 GB usable.

How much VRAM does R1 Distill 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 R1 Distill 14B on an RTX 4090?

Our estimate is 39–55 tokens per second at Q8\_0\. It is not a measured benchmark.

What context length can I use?

At Q8\_0, our KV estimate supports up to about 16k tokens before the cache pushes the total over usable memory.

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