# Neural Architecture Search in Roboflow Train

Neural Architecture Search (NAS) is now available as a training engine for object detection and instance segmentation projects. Instead of manually tuning hyperparameters and running multiple separate training jobs, NAS automatically evaluates thousands of candidate architectures in a single run. This allows you to find the optimal balance of inference speed and accuracy tailored to your specific dataset and deployment hardware.

Using a unique weight-sharing strategy, NAS explores these configurations simultaneously at a fraction of the traditional compute cost. Once training is complete, you can evaluate the resulting models on a speed-vs-accuracy graph to deploy the version that best fits your performance requirements, often achieving better latency and accuracy than standard fine-tuning.

[Read the announcement post](https://blog.roboflow.com/train-with-neural-architecture-search/)

[See documentation](https://docs.roboflow.com/train/neural-architecture-search)

[Watch the walkthrough video](https://youtu.be/ZtGXkuo1qiE?si=cRws4H4c5JXBiZX5)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.roboflow.com/changelog/explore-by-month/april-2026/neural-architecture-search-in-roboflow-train.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.