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Can a M2 8GB run gpt-oss 20B (MoE, MXFP4)?

No. gpt-oss 20B (MoE, MXFP4) does not fit on M2 8GB: MXFP4 needs 15.1 GB and 5.4 GB is usable.

Hardware: M2 8GB · Model: gpt-oss 20B (MoE, MXFP4)

M2 8GB has 8 GB of unified memory and 100 GB/s of memory bandwidth. M3 8GB has the same memory and bandwidth, so the fit numbers match; this page is M2 8GB. The checker leaves macOS a share of unified memory, so Ollama can use 5.4 GB. gpt-oss 20B (MoE, MXFP4) (20.9B, 3.6B active, OpenAI) at MXFP4 is a 14 GB download and needs 15.1 GB with headroom for about 8k tokens.

Best quantMXFP4
Download size14 GB
Memory needed15.1 GB
Usable fast memory5.4 GB
Fitdoes not fit
Estimated speedno estimate, it does not fit
Commandollama run gpt-oss:20b

Smallest hardware that runs it: RTX 3060 8GB at MXFP4 (partial offload (slower), 15.1 GB needed, 7.5 GB usable, about 13 tok/s (estimate)). Can a RTX 3060 8GB run gpt-oss 20B (MoE, MXFP4)?

No smaller OpenAI model in this list fits M2 8GB.

Open M2 8GB 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