Can I Run DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB)?
作者： Jakub Rusinowski · 最后更新： 2026年6月26日
Yes
Yes — DeepSeek V4.1 Flash at Q3_K_M needs about 122.4 GB of the 144 GB usable on Mac Studio (M2 Ultra, 192 GB) (~21.6 GB spare), at ~61.4 tok/s (estimated), with room for about 262,144 tokens of context.
Confidence: medium · Recommended quantization: Q3_K_M · Estimated speed: ~61.4 tok/s
or compare on Vast.ai
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
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 | 569.4 GB | ✗ No | — | — | 568 GB |
| Q8_0 | 303.1 GB | ✗ No | — | — | 301.8 GB |
| Q6_K | 234.3 GB | ✗ No | — | — | 232.9 GB |
| Q5_K_M | 202.7 GB | ✗ No | — | — | 201.3 GB |
| Q4_K_M | 172.8 GB | ✗ No | — | — | 171.5 GB |
| Q3_K_M | 122.4 GB | ✓ Yes | 256K | ~61.4 tok/s | 121.1 GB |
| Q2_K | 94.7 GB | ✓ Yes | 256K | ~74.6 tok/s | 93.4 GB |
Which DeepSeek V4.1 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| DeepSeek V4.1 | 967.4 GB | ✗ Too large | — |
| DeepSeek V4.1 Flash | 172.8 GB | ✗ Too large | — |
What to watch out for
- Q3_K_M is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 2 larger variants of DeepSeek V4.1 do not fit and would need CPU offload or different hardware.
- 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- Superseded by the M3 Ultra, which is why it is often the better used buy for large-model work.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)?
Yes — DeepSeek V4.1 Flash at Q3_K_M needs about 122.4 GB of the 144 GB usable on Mac Studio (M2 Ultra, 192 GB) (~21.6 GB spare), at ~61.4 tok/s (estimated), with room for about 262,144 tokens of context.
Which quantization of DeepSeek V4.1 should I use on Mac Studio (M2 Ultra, 192 GB)?
Q3_K_M — it needs about 122.4 GB of the 144 GB available, downloads as roughly 121.1 GB, and runs at an estimated 61.4 tokens/sec with up to 256K of context.
What limits DeepSeek V4.1 on Mac Studio (M2 Ultra, 192 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
Other Models on Mac Studio (M2 Ultra, 192 GB)
DeepSeek V4.1 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | DeepSeek V4.1 model page | Check your hardware