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Can a M2 16GB run Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class)?

No. Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class) does not fit on M2 16GB: Default needs 27.7 GB and 10.7 GB is usable.

Hardware: M2 16GB · Model: Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class)

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. Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class) (74B, 9B active, NVIDIA) at Default is a 25 GB download and needs 27.7 GB with headroom for about 8k tokens.

Best quantDefault
Download size25 GB
Memory needed27.7 GB
Usable fast memory10.7 GB
Fitdoes not fit
Estimated speedno estimate, it does not fit
Commandollama run nemotron-3.5-bolt:74b-a9b

Smallest hardware that runs it: RTX 3090 24GB at Default (partial offload (slower), 27.7 GB needed, 23.5 GB usable, about 31 tok/s (estimate)). Can a RTX 3090 24GB run Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class)?

A smaller NVIDIA model that fits this hardware: Nemotron Labs Dory 1.0 4B at Q5_K_M (fits in fast memory, 4.5 GB). Can a M2 16GB run Nemotron Labs Dory 1.0 4B?

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