# Can I run R1 Distill 7B on an RTX 4090? | What Can I Run AI?

> Yes. R1 Distill 7B at FP16 needs about 18.5 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-7b/rtx-4090/

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**Yes.** R1 Distill 7B at FP16 needs about 18.5 GB, and the GeForce RTX 4090 has 24.0 GB usable at a \~4k context.

# Can I run R1 Distill 7B on an RTX 4090?

R1 Distill 7B at FP16 needs about 18.5 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 7B DeepSeek-R1 distill on Qwen. It is a reasoning-tuned small model, not the full 671B R1\. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

FP16 Fits with headroom

Memory needed

18.5 GB at FP16, \~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

40–56 estimate

[DeepSeek-R1-Distill-Qwen-7B](https://whatcanirunai.vercel.app/models/deepseek-r1-distill-qwen-7b/) · [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 | 6.3 GB          | Q4Fits   |
| Q8\_0    | 10.3 GB         | Q8Fits   |
| FP16     | 18.5 GB         | FP16Fits |

## Estimated tokens per second

Estimate: **40–56 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

At FP16, this machine has headroom out to about **64k tokens** under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.

__Context headroom for R1 Distill 7B on an RTX 4090 at FP16__
| Context | KV cache (FP16) | Total at FP16 | Verdict   |
| ------- | --------------- | ------------- | --------- |
| 4k      | 0.2 GB          | 18.5 GB       | Fits      |
| 8k      | 0.5 GB          | 18.8 GB       | Fits      |
| 16k     | 0.9 GB          | 19.2 GB       | Fits      |
| 32k     | 1.9 GB          | 20.2 GB       | Fits      |
| 64k     | 3.8 GB          | 22.0 GB       | Tight     |
| 128k    | 7.5 GB          | 25.8 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-7B model page](https://whatcanirunai.vercel.app/models/deepseek-r1-distill-qwen-7b/).

## Other hardware for R1 Distill 7B

* [R1 Distill 7B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-7b/rtx-3060-12gb/)Fits
* [R1 Distill 7B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-7b/rtx-3070-ti/)Fits
* [R1 Distill 7B on an Arc B580](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-7b/arc-b580/)Fits
* [R1 Distill 7B on a Mac mini 16GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-qwen-7b/mac-mini-m6-16/)Fits

## 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 7B on an RTX 4090?

Yes. R1 Distill 7B at FP16 needs about 18.5 GB, and the GeForce RTX 4090 has 24.0 GB usable.

How much VRAM does R1 Distill 7B need?

About 6.3 GB at Q4\_K\_M, 10.3 GB at Q8\_0 and 18.5 GB at FP16, estimated for a \~4k context.

How fast is R1 Distill 7B on an RTX 4090?

Our estimate is 40–56 tokens per second at FP16\. It is not a measured benchmark.

What context length can I use?

At FP16, our KV estimate supports up to about 64k 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/