← CanIRunLocal · All hardware · All models
Yes. DeepSeek R1 Distill Qwen 14B fits in fast memory on M2 Pro 16GB at Q4_K_M (10.3 GB needed, 10.7 GB usable), about 18 tok/s (estimate).
Hardware: M2 Pro 16GB · Model: DeepSeek R1 Distill Qwen 14B
M2 Pro 16GB has 16 GB of unified memory and 200 GB/s of memory bandwidth. M1 Pro 16GB has the same memory and bandwidth, so the fit numbers match; this page is M2 Pro 16GB. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. DeepSeek R1 Distill Qwen 14B (14.8B, DeepSeek) at Q4_K_M is a 9 GB download and needs 10.3 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 9 GB |
| Memory needed | 10.3 GB |
| Usable fast memory | 10.7 GB |
| Fit | fits in fast memory |
| Estimated speed | ~18 tok/s (estimate) |
| Command | ollama run deepseek-r1:14b |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
A project by OnDevice Labs · llms.txt