NVIDIA Nemotron AI agent models now span enterprise servers and local PCs. The company’s open lineup includes Nemotron 3.5 Super VL, a 120-billion-parameter model for complex workflows, plus two smaller Bolt models designed for local hardware. NVIDIA announced the models on October 15.
Nemotron 3.5 Super VL combines reasoning, tool use, and text, image, document, and video understanding in one model. NVIDIA says it delivers up to five times the throughput of other open models in its size class, based on the company’s evaluations. Details are available in NVIDIA’s official announcement.
Smaller Nemotron models target local AI agents
Nemotron 3.5 Bolt 74B-A9B is designed to fit within 24GB of memory using 2-bit quantization. NVIDIA says it can run local agent tasks such as web research, writing, and code debugging on supported NVIDIA systems. It supports tools including llama.cpp, Ollama, LM Studio, Unsloth, and vLLM.
The smaller Nemotron 3.5 Bolt E4B targets conversational and embedded agents, including local voice assistants and interactive interfaces. NVIDIA lists October 23 as its planned release date, so it should not be described as generally available before then.
The announcement extends NVIDIA’s open-model strategy beyond large server deployments. It follows the company’s earlier Nemotron 3 Embed release for retrieval-augmented generation and agentic retrieval, while other companies are also developing business-focused agents, including Meta’s Muse AI agent for small businesses.
The practical distinction is hardware and workload: Super VL targets complex, multimodal enterprise tasks, while Bolt models are designed for tighter memory budgets and local use. NVIDIA’s performance figures are company-reported benchmarks, so real-world results will depend on the hardware, software stack, and task.
