Nemotron 3.5 — local AI model by NVIDIA
Written by Jakub Rusinowski · Last updated
NVIDIA's agentic line, built on a hybrid stack that interleaves Mamba-2 state-space layers and MoE blocks with a minority of attention layers. Only the attention layers hold a KV cache, which is what lets it advertise a 1M-token context at this size.
Variants
The smallest Nemotron 3.5 variant needs about 19 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache.
| Model | VRAM at Q4 | VRAM | Context | Run it |
|---|---|---|---|---|
| Nemotron 3.5 Lightning 30B-A3B → 30B (3B active) | ~18.9 GB | 1,000,000 | ollama run nemotron-3.5-lightning:30b | |
| Nemotron 3.5 Bolt 74B → 74B (9B active) | ~22.8 GB | 262,144 | ollama run nemotron-3.5-bolt:74b-a9b | |
| Nemotron 3.5 Super VL 120B-A12B → 120B (12B active) | ~73.3 GB | 1M | ollama run nemotron-3.5-super:120b |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Nemotron 3.5 locally
Install Ollama, then pull the tag.
ollama run nemotron-3.5-lightning:30bPick a size above for its own VRAM figure, speed estimate and install command.
Licence
Commercial use permitted. No usage restrictions beyond attribution.
Applies to: Nemotron 3.5 Lightning 30B-A3B, Nemotron 3.5 Bolt 74B, Nemotron 3.5 Super VL 120B-A12BRecommended GPU
The cheapest catalogued GPU that runs Nemotron 3.5 locally (min 19 GB VRAM) is the AMD Radeon RX 7900 XTX (24 GB).
Can I run Nemotron 3.5 on my GPU?
Nemotron 3.5 — frequently asked questions
How much VRAM does Nemotron 3.5 need?
Nemotron 3.5 needs about 19 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Nemotron 3.5 Lightning 30B-A3B (19 GB, Q4_K_M); Nemotron 3.5 Bolt 74B (23 GB, IQ2_XXS QAD); Nemotron 3.5 Super VL 120B-A12B (73 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Nemotron 3.5 on an RTX 4090 (24 GB)?
Yes — Nemotron 3.5 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for Nemotron 3.5?
Q4_K_M is the best balance of quality and VRAM for Nemotron 3.5 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Nemotron 3.5 with Ollama?
Install Ollama, then run: ollama run nemotron-3.5-lightning:30b. This downloads Nemotron 3.5 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.