text model · DeepSeek-R1-Distill · macOS
Can I run DeepSeek-R1-Distill-Qwen 32B on Apple M5 (16GB)?
No. DeepSeek-R1-Distill-Qwen 32B needs ~22.1 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.
Needs ~22.1 GB even at Q4_K_M, but only ~10.5 GB is usable.
- Q4_K_M needed
- ~22.1 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
- Parameters
- 32B
- Q4_K_M size
- 19.85 GB
- Q8_0 size
- 34.82 GB
- Context
- 128k
- Ollama tag
- deepseek-r1:32b
- Memory
- 16 GB unified
- Usable for weights
- ~10.5 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
What you can run instead
Run DeepSeek-R1-Distill-Qwen 32B on other hardware
FAQ
Can Apple M5 (16GB) run DeepSeek-R1-Distill-Qwen 32B?
No. DeepSeek-R1-Distill-Qwen 32B needs ~22.1 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.
How much memory does DeepSeek-R1-Distill-Qwen 32B need?
Apple M5 (16GB) does not have enough memory. At Q4_K_M the weights are ~19.85 GB; with KV cache and runtime overhead, budget ~22.1 GB at a 4k context.
What is the best tool to run DeepSeek-R1-Distill-Qwen 32B 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.