text model · DeepSeek-R1 · macOS
Can I run DeepSeek R1 on Apple M4 Max (64GB)?
No. DeepSeek R1 needs ~383.7 GB even at Q4_K_M, but Apple M4 Max (64GB) only has ~48 GB usable.
Needs ~383.7 GB even at Q4_K_M, but only ~48 GB is usable.
- Q4_K_M needed
- ~383.7 GB
- Usable on device
- ~48 GB
- Device memory
- 64 GB
- Parameters
- 671B (MoE, 37B active)
- Q4_K_M size
- 376.66 GB
- Context
- 128k
- Ollama tag
- deepseek-r1:671b
- Memory
- 64 GB unified
- Usable for weights
- ~48 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
What you can run instead
FAQ
Can Apple M4 Max (64GB) run DeepSeek R1?
No. DeepSeek R1 needs ~383.7 GB even at Q4_K_M, but Apple M4 Max (64GB) only has ~48 GB usable.
How much memory does DeepSeek R1 need?
Apple M4 Max (64GB) does not have enough memory. At Q4_K_M the weights are ~376.66 GB; with KV cache and runtime overhead, budget ~383.7 GB at a 4k context. It is a Mixture-of-Experts model (671B total / 37B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run DeepSeek R1 on macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
Sources
Memory figures are estimates. See methodology.