# NVIDIA Nemotron Nano v2: Long-Context Reasoning and Efficient Inference in Smaller Models

DevFeed: [NVIDIA Nemotron Nano v2: Long-Context Reasoning and Efficient Inference in Smaller Models](<https://devfeed.tech/articles/the-future-of-agentic-ai-is-small-35023.md>)

Original publisher: [Read original article](<https://read.theaimerge.com/p/the-future-of-agentic-ai-is-small>)

Author: Alex Razvant

Published: 2025-11-15T14:47:33Z

Content type: article

Language: en

Sources: [Neural Bits](<https://devfeed.tech/sources/neural-bits.md>)

Topics: [Nemotron](<https://devfeed.tech/topics/nemotron.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [model architecture](<https://devfeed.tech/topics/model-architecture.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Transformer](<https://devfeed.tech/topics/transformer.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [ai-ml](<https://devfeed.tech/tags/ai-ml.md>), [inference](<https://devfeed.tech/tags/inference.md>), [long-context](<https://devfeed.tech/tags/long-context.md>), [model-architecture](<https://devfeed.tech/tags/model-architecture.md>), [moe](<https://devfeed.tech/tags/moe.md>), [nemotron](<https://devfeed.tech/tags/nemotron.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>)

## AI overview

This technical article examines NVIDIA's Nemotron Nano v2 Transformer-Hybrid models, focusing on their long-context reasoning, fast inference, and reported performance against larger open models. It also describes the broader Nemotron family's open models, datasets, and fine-tuning recipes for agentic AI systems.

## Source excerpt

How NVIDIA's Nemotron Nano V2 SLM, built for long-context reasoning, fast inference, can compete with models 4-5x its size.