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Can a M2 16GB run Gemma 4 E2B (effective 2.3B)?

Yes. Gemma 4 E2B (effective 2.3B) fits in fast memory on M2 16GB at Q8_0 (7.2 GB needed, 10.7 GB usable), about 13 tok/s (estimate).

Hardware: M2 16GB · Model: Gemma 4 E2B (effective 2.3B)

M2 16GB has 16 GB of unified memory and 100 GB/s of memory bandwidth. M3 16GB has the same memory and bandwidth, so the fit numbers match; this page is M2 16GB. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. Gemma 4 E2B (effective 2.3B) (5.12B, Google) at Q8_0 is a 6 GB download and needs 7.2 GB with headroom for about 8k tokens.

Best quantQ8_0
Download size6 GB
Memory needed7.2 GB
Usable fast memory10.7 GB
Fitfits in fast memory
Estimated speed~13 tok/s (estimate)
Commandollama run gemma4:e2b-it-q8_0
Open M2 16GB in the checker

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