← CanIRunLocal · All hardware · All models
Yes. Qwen 2.5 Coder 14B fits in fast memory on M4 Max (40c GPU) 128GB at Q8_0 (17.3 GB needed, 96.0 GB usable), about 27 tok/s (estimate).
Hardware: M4 Max (40c GPU) 128GB · Model: Qwen 2.5 Coder 14B
M4 Max (40c GPU) 128GB has 128 GB of unified memory and 546 GB/s of memory bandwidth. Mac Studio M4 Max (40c GPU) 128GB has the same memory and bandwidth, so the fit numbers match; this page is M4 Max (40c GPU) 128GB. The checker leaves macOS a share of unified memory, so Ollama can use 96.0 GB. Qwen 2.5 Coder 14B (14.8B, Alibaba) at Q8_0 is a 16 GB download and needs 17.3 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 16 GB |
| Memory needed | 17.3 GB |
| Usable fast memory | 96.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~27 tok/s (estimate) |
| Command | ollama run qwen2.5-coder:14b-instruct-q8_0 |
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