Can I run it?

Can I run Qwen2.5 14B Instruct on Apple M4 Pro?

Tight fit

Tight fit fully in unified memory on your Apple M4 Pro at Q8_0, 8K context, about 8.7–12 tok/s. Weights 14.6 GB plus 1.50 GB of KV cache — 16.6 GB of 18.0 GB usable.

Best quantQ8_0

Working context8K

Max that fits8K

Speed8.7–12 tok/s

Weights14.6 GB

KV cache1.50 GB

Total16.6 GB

Usable18.0 GB

Qwen2.5 14B Instruct details · Apple M4 Pro page · How this estimate is made

Run commands

llama.cpp

llama-server -hf bartowski/Qwen2.5-14B-Instruct-GGUF:Q8_0 -c 8192 -ngl 48

Ollama

ollama run qwen2.5

LM Studio

lms get bartowski/Qwen2.5-14B-Instruct-GGUF
# Then load quant Q8_0

Assumptions

Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
Q8_0 size is the real GGUF file size from Hugging Face.
Unified memory uses 75% for the GPU by default, and always leaves about 5 GB for the OS.
Speed is quoted at 8K context, not at the maximum context that still fits.

Larger models that also fit

Can I run Qwen3.8 27B on Apple M4 Pro? — Tight fit, UD-Q4_K_XL, 8.3–11 tok/s
Can I run Qwen3.6 35B A3B on Apple M4 Pro? — Tight fit, UD-IQ4_XS, 88–120 tok/s
Can I run Qwen3.8 35B A3B Distill on Apple M4 Pro? — Tight fit, Q3_K_M, 90–123 tok/s

Updated 2026-10-17. Profile on this page is the device default.