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Can a M1 16GB run GLM-4.7-Flash 30B-A3B (MoE)?

No. GLM-4.7-Flash 30B-A3B (MoE) does not fit on M1 16GB: Q4_K_M needs 20.4 GB and 10.7 GB is usable.

Hardware: M1 16GB · Model: GLM-4.7-Flash 30B-A3B (MoE)

M1 16GB has 16 GB of unified memory and 68 GB/s of memory bandwidth. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. GLM-4.7-Flash 30B-A3B (MoE) (31.2B, 3B active, Z.ai) at Q4_K_M is a 19 GB download and needs 20.4 GB with headroom for about 8k tokens.

Best quantQ4_K_M
Download size19 GB
Memory needed20.4 GB
Usable fast memory10.7 GB
Fitdoes not fit
Estimated speedno estimate, it does not fit
Commandollama run glm-4.7-flash:latest

Smallest hardware that runs it: RTX 3060 12GB at Q4_K_M (partial offload (slower), 20.4 GB needed, 11.5 GB usable, about 20 tok/s (estimate)). Can a RTX 3060 12GB run GLM-4.7-Flash 30B-A3B (MoE)?

A smaller Z.ai model that fits this hardware: GLM-OCR 0.9B at BF16 (fits in fast memory, 3.7 GB). Can a M1 16GB run GLM-OCR 0.9B?

Open M1 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