Nemotron 3.5 Lightning 30B-A3B
Nemotron 3.5 Lightning 30B-A3B loads in 23.7 GB at Q4_K_M and decodes at the speed of its 3B active path, comfortably from 36 GB of memory, Macs included, starting at the MacBook Pro M5 Pro 48GB. Below is the memory math we ran for it, the smallest card that fits, and the fastest machine we track.
How much memory does Nemotron 3.5 Lightning 30B-A3B need?
Nemotron 3.5 Lightning 30B-A3B is a 30B mixture-of-experts model (3B active per token) built for agentic, coding, long context. The weights alone take 23.7 GB at Q4_K_M; add context and the OS, and it belongs in the 36 GB memory class. Every number below comes from the ModelFit engine: speeds are estimates, labeled est., because we do not benchmark hardware ourselves.
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Which machines run Nemotron 3.5 Lightning 30B-A3B?
Verdicts come from the same engine that powers our fit checker: memory capacity first, bandwidth for speed. How we compute these numbers · Hugging Face model card
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Frequently asked questions
How much memory does Nemotron 3.5 Lightning 30B-A3B need?
23.7 GB for the Q4_K_M weights, plus ~0.1 GB of KV-cache at 16k context, about 23.8 GB total. Comfortable from 36 GB of VRAM or unified memory.
Does Nemotron 3.5 Lightning 30B-A3B run on a Mac?
Yes, from the MacBook Pro M5 Pro 48GB (~42 tok/s est.). Unified memory means the RAM budget is the only limit.
What is the smallest GPU for Nemotron 3.5 Lightning 30B-A3B?
The NVIDIA GeForce RTX 5090 (32 GB VRAM) is the smallest tracked card that runs Nemotron 3.5 Lightning 30B-A3B comfortably, ~125 tok/s est.
Cite this page
ModelFit: Nemotron 3.5 Lightning 30B-A3B, specs, memory math and hardware verdicts. https://modelfit.io/models/nemotron-3.5-lightning-30b/ (dataset updated 2026-10-13, CC BY 4.0).