Nemotron 3 Super fits into enterprise AI stacks as the reasoning layer — handling code generation, security analysis, and long-horizon planning — while Zilliz Cloud serves as the knowledge and memory layer that provides relevant context to each model call.
Modern enterprise AI stacks decompose into: data storage (object stores, databases), embedding generation (NeMo Retriever, Llama Nemotron Embed), vector storage (Zilliz Cloud), and reasoning (Nemotron 3 Super). Each component has a specialized role. Zilliz Cloud handles high-throughput embedding storage and low-latency retrieval, ensuring Nemotron 3 Super receives relevant context with every query rather than relying solely on its pre-training knowledge.
This architecture is modular: enterprises can swap the reasoning model without changing the vector storage layer, or scale Zilliz Cloud independently from the model serving cluster. NVIDIA's positioning of Zilliz at the center of its unstructured data story at GTC 2026 reflects this architectural reality. See how Zilliz ended up at the center of NVIDIA's unstructured data story at GTC 2026 for a detailed architectural overview.