# Can I run DeepSeek-R1 on dual RTX 3090s? | What Can I Run AI

> No. DeepSeek-R1 needs about 478.2 GB at Q4_K_M, and dual RTX 3090s has 48.0 GB usable. What to run instead.

Source: https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/dual-rtx-3090/

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**No.** DeepSeek-R1 at Q4\_K\_M needs about 478.2 GB, and dual RTX 3090s have 48.0 GB usable at a \~4k context.

# Can I run DeepSeek-R1 on dual RTX 3090s?

DeepSeek-R1 at Q4\_K\_M needs about 478.2 GB, and dual RTX 3090s have 48.0 GB usable. Two cards add memory, not decode speed; the speed estimate uses one RTX 3090’s 936 GB/s. The full DeepSeek-R1 teacher model (hundreds of billions of parameters). No single device we track holds it at Q4\. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks.

Quant that fits

None of Q4, Q8 or FP16 needs 478.2 GB

Memory needed

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

Usable VRAM

48.0 GB of 48 GB VRAM

Est. tokens/sec

n/a does not fit

[DeepSeek-R1](https://whatcanirunai.vercel.app/models/deepseek-r1/) · [GeForce RTX 3090](https://whatcanirunai.vercel.app/hardware/rtx-3090/) · [Multi-GPU](https://whatcanirunai.vercel.app/multi-gpu-for-local-llm/) · [Dual 3090 build](https://whatcanirunai.vercel.app/builds/dual-used-rtx-3090-70b/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3090/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)

## Memory at each quant

| Quant    | Need vs 48.0 GB | Verdict       |
| -------- | --------------- | ------------- |
| Q4\_K\_M | 478.2 GB        | Q4Won’t fit   |
| Q8\_0    | 837.4 GB        | Q8Won’t fit   |
| FP16     | 1575.3 GB       | FP16Won’t fit |

## Estimated tokens per second

No speed estimate: DeepSeek-R1 does not fit in the 48.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 32B](https://whatcanirunai.vercel.app/models/deepseek-r1-distill-qwen-32b/) instead (23.8 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
* No single device we track has enough usable memory for DeepSeek-R1 at Q4 (478.2 GB needed). A smaller distill or a hosted API is the practical path.
* 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/deepseek-r1/) and the [DeepSeek-R1 model page](https://whatcanirunai.vercel.app/models/deepseek-r1/).

## Other hardware for DeepSeek-R1

* [DeepSeek-R1 on a Mac Studio 512GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/mac-studio-m5-ultra-512/)Won’t fit
* [DeepSeek-R1 on a Mac Studio 256GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/mac-studio-m5-ultra-256/)Won’t fit
* [DeepSeek-R1 on an RTX 5090](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/rtx-5090/)Won’t fit
* [DeepSeek-R1 on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/rtx-4090/)Won’t fit

## Other models on dual RTX 3090s

* [Llama 3.3 70B on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/llama-3.3-70b-instruct/dual-rtx-3090/)Won’t fit
* [R1 Distill 70B on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1-distill-llama-70b/dual-rtx-3090/)Won’t fit
* [gpt-oss-120b on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-120b/dual-rtx-3090/)Won’t fit
* [Qwen3-235B on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/qwen3-235b-a22b/dual-rtx-3090/)Won’t fit
* [Mixtral 8x22B on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/mixtral-8x22b-instruct-v0.1/dual-rtx-3090/)Won’t fit
* [GLM-4.5-Air on dual RTX 3090s](https://whatcanirunai.vercel.app/can-i-run/glm-4.5-air/dual-rtx-3090/)Won’t fit

## Quick answers

Can I run DeepSeek-R1 on dual RTX 3090s?

No. DeepSeek-R1 at Q4\_K\_M needs about 478.2 GB, and dual RTX 3090s have 48.0 GB usable.

How much VRAM does DeepSeek-R1 need?

About 478.2 GB at Q4\_K\_M, 837.4 GB at Q8\_0 and 1575.3 GB at FP16, estimated for a \~4k context.

How fast is DeepSeek-R1 on dual RTX 3090s?

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

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