Your AI chip is powerful.
Your SDK should be too.

To fully unlock your AI chip’s performance, your software stack needs to match.

Integrate NetsPresso modules into your SDK and deliver optimized AI at the edge.

Partner with Us

Trusted by

AI Hub

Seamless
Integration with
Qualcomm AI Hub

Train and compress your models in NetsPresso, then compile and profile them seamlessly on Qualcomm AI Hub.

See Details

We've successfully ported hundreds of AI models across 100+ devices.

Now, it's your device's turn.
Which model would you like to optimize for your chip?

Modules designed to align
with your optimization workflow

Select only the features you need
— each module is decoupled and lightweight, making it easy to integrate into your existing pipeline or SDK.

Core Engine

Model Zoo

Trainer

Compressor

Graph Optimizer

Quantizer

IR Converter

Simulator

Profiler

Device Farm

Model Development

Model Optimization

Model Testing

Model Development

Task-specific lightweight models with high performance

Model zoo

Offers a variety of pre-trained models compatible with your target device.

Trainer

Supports customized model training using your own dataset.

Compressor

Generates lightweight models through structured pruning and filter decomposition.

Model Optimization

Maximize model performance
for your chip

Graph Optimizer

Optimizes model architecture by merging operations and removing unnecessary computations.

Quantizer

Reduces computation by lowering model precision (e.g., FP32 → INT8), improving execution efficiency on devices.

IR Converter

Converts models from various frameworks into IR format compatible with your SDK.

Model Testing

Quickly and accurately validate performance on real devices

Simulator

Measures quantitative performance metrics before and after optimization.

Profiler

Analyzes model performance on your device, including inference time and memory usage, and identifies bottlenecks.

Device Farm

Provides a testing infrastructure to run and compare models across a wide range of real devices.

Code it. Click it.
Your workflow, your choice.

Whether you prefer code or clicks, choose the interface that fits your workflow — Python CLI for full control, or GUI for visual insights and ease of use.

Logo

Github Repository

Model Development

Model Optimization

Model Testing

Train models in your local environment and apply compression techniques like pruning and filter decomposition to build efficient, lightweight models.

Installation Guide

Go to the site

Go to the site

Why NetsPresso?

Ensures model–device compatibility

Automatically resolves operator mismatches and supports quantization to match target device constraints.

Enhances optimization quality

Enables flexible model framework support

Provides efficient modular SDK integration

Supports real-device validation

Offers both GUI and CLI access

Optimize what matters
- make it compatible, fast, and real.

Start Integration

netspresso@nota.ai

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