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Yes. Gemma 3n E4B (on-device) fits in fast memory on Mac Studio M5 Ultra (64c GPU) 96GB at Q8_0 (10.5 GB needed, 72.0 GB usable), about 101 tok/s (estimate).
Hardware: Mac Studio M5 Ultra (64c GPU) 96GB · Model: Gemma 3n E4B (on-device)
Mac Studio M5 Ultra (64c GPU) 96GB has 96 GB of unified memory and 1200 GB/s of memory bandwidth. Mac Studio M5 Ultra (80c GPU) 96GB has the same memory and bandwidth, so the fit numbers match; this page is Mac Studio M5 Ultra (64c GPU) 96GB. The checker leaves macOS a share of unified memory, so Ollama can use 72.0 GB. Gemma 3n E4B (on-device) (8B, Google) at Q8_0 is a 9.5 GB download and needs 10.5 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 9.5 GB |
| Memory needed | 10.5 GB |
| Usable fast memory | 72.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~101 tok/s (estimate) |
| Command | ollama run gemma3n:e4b-it-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