HomeCan I run it?DeepSeek-V3.2DeepSeek-V3.2 on a Mac Studio 256GB
No. DeepSeek-V3.2 at Q4_K_M needs about 478.8 GB, and the Mac Studio M5 Ultra 256GB has 192.0 GB usable at a ~4k context.
Can I run DeepSeek-V3.2 on a Mac Studio 256GB?
DeepSeek-V3.2 at Q4_K_M needs about 478.8 GB, and the Mac Studio M5 Ultra 256GB has 192.0 GB usable. That figure is 256 GB of unified memory on the spec sheet, of which 192.0 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, 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
- 192.0 GB of 256 GB unified memory
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 192.0 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No speed estimate: DeepSeek-V3.2 does not fit in the 192.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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-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 We do not publish an offload tokens/sec figure.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. Specs for this machine: Mac Studio M5 Ultra 256GB.
Other hardware for DeepSeek-V3.2
- DeepSeek-V3.2 on a Mac Studio 512GBWon’t fit
- DeepSeek-V3.2 on an RTX 5090Won’t fit
- DeepSeek-V3.2 on an RTX 4090Won’t fit
Other models on a Mac Studio 256GB
- Llama 3.3 70B on a Mac Studio 256GBFits
- R1 Distill 70B on a Mac Studio 256GBFits
- gpt-oss-120b on a Mac Studio 256GBFits
- Qwen3-235B on a Mac Studio 256GBFits
- DeepSeek-R1 on a Mac Studio 256GBWon’t fit
- Mixtral 8x22B on a Mac Studio 256GBTight
Quick answers
- Can I run DeepSeek-V3.2 on a Mac Studio 256GB?
- No. DeepSeek-V3.2 at Q4_K_M needs about 478.8 GB, and the Mac Studio M5 Ultra 256GB has 192.0 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 256GB?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.