NVIDIA releases Nemotron 3.5 Super VL and two Bolt edge models
NVIDIA released Nemotron 3.5 Super VL on Oct. 15, an open multimodal model with 120B total and 12B active parameters in a mixture-of-experts design that combines reasoning, instruction following and tool use with text, image, document and video understanding for long-running agents. NVIDIA claims it reaches up to 5x the agentic throughput of other open models in its size class on a single GPU — over 600 output tokens per second at 100,000 input tokens — scores 80.8% on the CharXiv chart-reasoning benchmark (84% with Python code interpretation), and supports NVFP4 quantization and multi-token prediction; BF16 and NVFP4 weights are on Hugging Face with same-day vLLM and Baseten support. Alongside it, NVIDIA launched two Nemotron 3.5 Bolt edge models: Bolt 74B-A9B 24GB, which uses native 2-bit quantization to fit in 24GB of memory and is available now, and Bolt E4B 4GB, due Oct. 23.
An open-weight model that folds visual understanding into agentic execution lets teams post-train and self-host vision-capable agents instead of relying on closed frontier APIs.