text model · DeepSeek-R1-Distill · macOS
Can I run DeepSeek-R1-Distill-Qwen 14B on Apple M4 (16GB)?
No. DeepSeek-R1-Distill-Qwen 14B needs ~10.7 GB even at Q4_K_M, but Apple M4 (16GB) only has ~10.5 GB usable.
Needs ~10.7 GB even at Q4_K_M, but only ~10.5 GB is usable.
- Q4_K_M needed
- ~10.7 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
- Parameters
- 14B
- Q4_K_M size
- 8.99 GB
- Q8_0 size
- 15.7 GB
- Context
- 128k
- Ollama tag
- deepseek-r1:14b
- Memory
- 16 GB unified
- Usable for weights
- ~10.5 GB
- Best runtime
- Ollama (MLX backend, preview) / MLX direct
What you can run instead
Run DeepSeek-R1-Distill-Qwen 14B on other hardware
FAQ
Can Apple M4 (16GB) run DeepSeek-R1-Distill-Qwen 14B?
No. DeepSeek-R1-Distill-Qwen 14B needs ~10.7 GB even at Q4_K_M, but Apple M4 (16GB) only has ~10.5 GB usable.
How much memory does DeepSeek-R1-Distill-Qwen 14B need?
Apple M4 (16GB) does not have enough memory. At Q4_K_M the weights are ~8.99 GB; with KV cache and runtime overhead, budget ~10.7 GB at a 4k context.
What is the best tool to run DeepSeek-R1-Distill-Qwen 14B 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.