Nemotron Nano 9B V2
Nemotron Nano 9B V2 is NVIDIA's second-generation 9-billion-parameter model in the Nemotron Nano series, optimized for deployment on edge devices, workstations, and resource-constrained environments. NVIDIA designed this model to deliver capable language understanding and generation within a footprint that can run efficiently without data-center-scale infrastructure.
V2 improves on the first-generation Nano model in instruction following and factual accuracy, while maintaining its small size advantage for on-device use cases. It is particularly relevant for enterprise edge deployments, local AI assistants, and applications where data privacy or latency requirements preclude cloud-based inference. The model aligns with NVIDIA's broader push to bring AI inference to the edge through its hardware and software ecosystem.
Key Features
9B parameter scale optimized for edge and on-device deployment
Improved instruction following and response quality over V1
Low memory footprint enabling local inference on workstations and edge hardware
Suitable for data-privacy-sensitive workflows not appropriate for cloud APIs
Aligned with NVIDIA's NeMo framework and TensorRT-LLM optimization pipeline
Ideal Use Cases
On-device AI assistant for enterprise workstations and air-gapped environments
Edge inference for IoT and industrial AI applications
Local document summarization and extraction without cloud dependency
Privacy-preserving AI tooling for regulated industries like healthcare and finance
Example Prompts for Nemotron Nano 9B V2
Technical Specifications
| Provider | Nvidia |
| Category | Text |
| Modality | Text -> Text |
Frequently Asked Questions
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