Can I Run DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 25 października 2026
No
No — DeepSeek V4.1 does not fit in Mac Studio (M2 Ultra, 192 GB). Even at Q2_K it needs about 252.3 GB against 144 GB usable, a shortfall of roughly 108.3 GB.
Confidence: medium
Get a personalized upgrade path →
Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.
Mac Studio (M2 Ultra, 192 GB) — what it gives a model
| Usable memory for models | 144 GB |
| Memory bandwidth | 800 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB): memory by quantization
| Quant | Memory needed | Fits 144 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 1527.8 GB | ✗ No | — | — | 1526.4 GB |
| Q8_0 | 812.3 GB | ✗ No | — | — | 810.9 GB |
| Q6_K | 627.2 GB | ✗ No | — | — | 625.8 GB |
| Q5_K_M | 542.3 GB | ✗ No | — | — | 540.9 GB |
| Q4_K_M | 462.2 GB | ✗ No | — | — | 460.8 GB |
| Q3_K_M | 326.7 GB | ✗ No | — | — | 325.3 GB |
| Q2_K | 252.3 GB | ✗ No | — | — | 250.9 GB |
What to watch out for
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Mac Studio M2 Ultra 192 GB limitations
- Superseded by the M3 Ultra, which is why it is often the better used buy for large-model work.
- Memory is soldered; the configuration chosen at purchase is permanent.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 192 GB unified memory at 800 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB)?
No — DeepSeek V4.1 does not fit in Mac Studio (M2 Ultra, 192 GB). Even at Q2_K it needs about 252.3 GB against 144 GB usable, a shortfall of roughly 108.3 GB.
What limits DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB)?
Memory. Mac Studio (M2 Ultra, 192 GB) provides about 144 GB usable, and the smallest quantization of this model needs 252.3 GB.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Models on Mac Studio (M2 Ultra, 192 GB)
- Devstral on Mac Studio (M2 Ultra, 192 GB)
- EXAONE 3.5 on Mac Studio (M2 Ultra, 192 GB)
- Falcon 3 on Mac Studio (M2 Ultra, 192 GB)
- Gemma 2 Family on Mac Studio (M2 Ultra, 192 GB)
- Gemma 3 on Mac Studio (M2 Ultra, 192 GB)
DeepSeek V4.1 on GPUs
- DeepSeek V4.1 on Apple M4 Max
- DeepSeek V4.1 on Apple M2 Ultra
- DeepSeek V4.1 on Apple M2 Max
- DeepSeek V4.1 on Apple M1 Ultra
What This Model Is Good At
Model & Tools
← Can I Run It? | DeepSeek V4.1 model page | Check your hardware