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No. Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class) does not fit on M1 Max (24c GPU) 32GB: Default needs 27.7 GB and 24.0 GB is usable.
Hardware: M1 Max (24c GPU) 32GB · Model: Nemotron 3.5 Bolt 74B-A9B (MoE, IQ2-class)
M1 Max (24c GPU) 32GB has 32 GB of unified memory and 400 GB/s of memory bandwidth. M1 Max (32c GPU) 32GB and M2 Max (30c GPU) 32GB and M2 Max (38c GPU) 32GB have the same memory and bandwidth, so the fit numbers match; this page is M1 Max (24c GPU) 32GB. The checker leaves macOS a share of unified memory, so Ollama can use 24.0 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 quant | Default |
|---|---|
| Download size | 25 GB |
| Memory needed | 27.7 GB |
| Usable fast memory | 24.0 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama 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 M1 Max (24c GPU) 32GB run Nemotron Labs Dory 1.0 4B?
Open M1 Max (24c GPU) 32GB in the checkerEstimates, 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.
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