Can I Run DeepSeek V4 on Mac Studio (M3 Ultra, 256 GB)?
Written by Jakub Rusinowski · Last updated April 24, 2026
Yes
Yes — DeepSeek V4-Flash at Q4_K_M needs about 172.8 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB) (~19.2 GB spare), at ~47.3 tok/s (estimated), with room for about 262,144 tokens of context.
Confidence: medium · Recommended quantization: Q4_K_M · Estimated speed: ~47.3 tok/s
Mac Studio (M3 Ultra, 256 GB) — what it gives a model
| Usable memory for models | 192 GB |
| Memory bandwidth | 819 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
DeepSeek V4 on Mac Studio (M3 Ultra, 256 GB): memory by quantization
| Quant | Memory needed | Fits 192 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 | ✓ Yes | 256K | ~47.3 tok/s | 171.5 GB |
| Q3_K_M | 122.4 GB | ✓ Yes | 256K | ~62.6 tok/s | 121.1 GB |
| Q2_K | 94.7 GB | ✓ Yes | 256K | ~76 tok/s | 93.4 GB |
Which DeepSeek V4 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| DeepSeek V4-Pro | 967.4 GB | ✗ Too large | — |
| DeepSeek V4-Flash | 172.8 GB | ✓ Fits | ~47.3 tok/s |
What to watch out for
- 1 larger variant of DeepSeek V4 does 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 M3 Ultra 256 GB limitations
- The largest single-box unified memory pool available, but at roughly half the memory bandwidth of a high-end discrete GPU — very large models load, then run slowly.
- 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.
- 256 GB unified memory at 819 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 on Mac Studio (M3 Ultra, 256 GB)?
Yes — DeepSeek V4-Flash at Q4_K_M needs about 172.8 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB) (~19.2 GB spare), at ~47.3 tok/s (estimated), with room for about 262,144 tokens of context.
Which quantization of DeepSeek V4 should I use on Mac Studio (M3 Ultra, 256 GB)?
Q4_K_M — it needs about 172.8 GB of the 192 GB available, downloads as roughly 171.5 GB, and runs at an estimated 47.3 tokens/sec with up to 256K of context.
What limits DeepSeek V4 on Mac Studio (M3 Ultra, 256 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 Models on Mac Studio (M3 Ultra, 256 GB)
DeepSeek V4 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | DeepSeek V4 model page | Check your hardware