NVIDIA open-sources Nemotron 3.5 Bolt 74B VLM that fits local agents in 24GB via native 2-bit quant
jacek2023 · reddit · 2026-10-15
NVIDIA released Nemotron 3.5 Bolt 74B-A9B 24GB, a vision-language model designed to run everyday agentic tasks locally within 24GB of memory.
Key specs:
- Architecture: Mamba-2–Transformer hybrid LatentMoE with a C-RADIO v4-H vision encoder; 74B total / 9B active parameters
- Quantization: native 2-bit (IQ2) quantization-aware training, so it can run alongside other apps
- Context: up to 256K tokens; accepts text, image, and video input
- Speed: LiLiCorr speculative decoding drafter via DFlash (7 tokens) in companion vLLM recipes
- Deployment: vLLM on Ampere, Hopper, or Blackwell GPUs
- License: OpenMDW-1.1, open for commercial and non-commercial use
NVIDIA claims it is faster than most popular dense models while smarter than similar-footprint MoE models, optimizing intelligence and speed per GB.
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