HomeCan I run it?DeepSeek-R1DeepSeek-R1 on a Mac Studio 512GB
No. DeepSeek-R1 at Q4_K_M needs about 478.2 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable at a ~4k context.
Can I run DeepSeek-R1 on a Mac Studio 512GB?
DeepSeek-R1 at Q4_K_M needs about 478.2 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. 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, 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 unified memory
- 384.0 GB of 512 GB unified memory
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 384.0 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No speed estimate: DeepSeek-R1 does not fit in the 384.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 to explore longer chats.
What to do instead
- Run Qwen3-235B 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-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 We do not publish an offload tokens/sec figure.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 and the DeepSeek-R1 model page.
Other hardware for DeepSeek-R1
- DeepSeek-R1 on a Mac Studio 256GBWon’t fit
- DeepSeek-R1 on dual RTX 3090sWon’t fit
- DeepSeek-R1 on an RTX 5090Won’t fit
- DeepSeek-R1 on an RTX 4090Won’t fit
Other models on a Mac Studio 512GB
- Llama 3.3 70B on a Mac Studio 512GBFits
- gpt-oss-120b on a Mac Studio 512GBFits
- Qwen3-235B on a Mac Studio 512GBFits
- DeepSeek-V3.2 on a Mac Studio 512GBWon’t fit
Quick answers
- Can I run DeepSeek-R1 on a Mac Studio 512GB?
- No. DeepSeek-R1 at Q4_K_M needs about 478.2 GB, and the Mac Studio M5 Ultra 512GB has 384.0 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 a Mac Studio 512GB?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.