# Can I run DeepSeek-V3.2 on a Mac Studio 512GB?

> No. DeepSeek-V3.2 needs about 478.8 GB at Q4_K_M, and Mac Studio 512GB has 384.0 GB usable. What to run instead.

Source: https://whatcanirunai.vercel.app/can-i-run/deepseek-v3.2/mac-studio-m5-ultra-512/

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**No.** DeepSeek-V3.2 at Q4\_K\_M needs about 478.8 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable at a \~4k context.

# Can I run DeepSeek-V3.2 on a Mac Studio 512GB?

DeepSeek-V3.2 at Q4\_K\_M needs about 478.8 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable. That figure is 512 GB of unified memory on the spec sheet, of which 384.0 GB is usable for weights and cache, at 1200 GB/s memory bandwidth. DeepSeek’s large V3.2 model. Like full R1, it is far beyond a single consumer GPU or current Mac Studio 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 478.8 GB

Memory needed

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

Usable unified memory

384.0 GB of 512 GB unified memory

Est. tokens/sec

n/a does not fit

[DeepSeek-V3.2](https://whatcanirunai.vercel.app/models/deepseek-v3.2/) · [Mac Studio M5 Ultra 512GB](https://whatcanirunai.vercel.app/hardware/mac-studio-m5-ultra-512/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/mac-studio-m5-ultra-512/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)

## Memory at each quant

| Quant    | Need vs 384.0 GB | Verdict       |
| -------- | ---------------- | ------------- |
| Q4\_K\_M | 478.8 GB         | Q4Won’t fit   |
| Q8\_0    | 838.4 GB         | Q8Won’t fit   |
| FP16     | 1577.3 GB        | FP16Won’t fit |

## Estimated tokens per second

No speed estimate: DeepSeek-V3.2 does not fit in the 384.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 [Qwen3-235B](https://whatcanirunai.vercel.app/can-i-run/qwen3-235b-a22b/mac-studio-m5-ultra-512/) instead (164.9 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-V3.2 at Q4 (478.8 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.
* Full hardware list: [DeepSeek-V3.2](https://whatcanirunai.vercel.app/models/deepseek-v3.2/). Specs for this machine: [Mac Studio M5 Ultra 512GB](https://whatcanirunai.vercel.app/hardware/mac-studio-m5-ultra-512/).

## Other hardware for DeepSeek-V3.2

* [DeepSeek-V3.2 on a Mac Studio 256GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-v3.2/mac-studio-m5-ultra-256/)Won’t fit
* [DeepSeek-V3.2 on an RTX 5090](https://whatcanirunai.vercel.app/can-i-run/deepseek-v3.2/rtx-5090/)Won’t fit
* [DeepSeek-V3.2 on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/deepseek-v3.2/rtx-4090/)Won’t fit

## Other models on a Mac Studio 512GB

* [Llama 3.3 70B on a Mac Studio 512GB](https://whatcanirunai.vercel.app/can-i-run/llama-3.3-70b-instruct/mac-studio-m5-ultra-512/)Fits
* [gpt-oss-120b on a Mac Studio 512GB](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-120b/mac-studio-m5-ultra-512/)Fits
* [Qwen3-235B on a Mac Studio 512GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-235b-a22b/mac-studio-m5-ultra-512/)Fits
* [DeepSeek-R1 on a Mac Studio 512GB](https://whatcanirunai.vercel.app/can-i-run/deepseek-r1/mac-studio-m5-ultra-512/)Won’t fit

## Quick answers

Can I run DeepSeek-V3.2 on a Mac Studio 512GB?

No. DeepSeek-V3.2 at Q4\_K\_M needs about 478.8 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable.

How much VRAM does DeepSeek-V3.2 need?

About 478.8 GB at Q4\_K\_M, 838.4 GB at Q8\_0 and 1577.3 GB at FP16, estimated for a \~4k context.

How fast is DeepSeek-V3.2 on a Mac Studio 512GB?

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

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