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.

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?

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?

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

Modules designed to align
with your optimization workflow

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

Model Optimization

Model Testing

Model Development

Task-specific lightweight models with high performance

Task-specific lightweight models with high performance

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

Maximize model performance
for your chip

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

Quickly and accurately validate performance on real devices

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.

Download

Opens May 21

Go to the site

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.

Download

Opens May 21

Go to the site

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

Download

Optimize AI model efficiency and hardware compatibility through graph optimization and mixed-precision quantization.

Opens May 21

Convert and benchmark models to validate compatibility, speed, and memory usage directly on real devices.

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 advanced compression and quantization while maintaining accuracy and improving speed.

Enables flexible model framework support

Allows seamless transformation of models across frameworks via an IR conversion layer.

Provides efficient modular SDK integration

Each function is modularized so users can selectively use training, optimization, and testing stages.

Supports real-device validation

Framer is an end to end tool that lets everyone design and ship web sites. You don’t need a frontend team or web programming course. Just basic canvas skills.

Offers both GUI and CLI access

GUI for intuitive visual flows and Python SDK for advanced automation and customization.

Ensures model–device compatibility

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

Enhances optimization quality

Enables advanced compression and quantization while maintaining accuracy and improving speed.

Enables flexible model framework support

Allows seamless transformation of models across frameworks via an IR conversion layer.

Provides efficient modular SDK integration

Each function is modularized so users can selectively use training, optimization, and testing stages.

Supports real-device validation

Framer is an end to end tool that lets everyone design and ship web sites. You don’t need a frontend team or web programming course. Just basic canvas skills.

Offers both GUI and CLI access

GUI for intuitive visual flows and Python SDK for advanced automation and customization.

Ensures model–device compatibility

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

Enhances optimization quality

Enables advanced compression and quantization while maintaining accuracy and improving speed.

Enables flexible model framework support

Allows seamless transformation of models across frameworks via an IR conversion layer.

Provides efficient modular SDK integration

Each function is modularized so users can selectively use training, optimization, and testing stages.

Supports real-device validation

Framer is an end to end tool that lets everyone design and ship web sites. You don’t need a frontend team or web programming course. Just basic canvas skills.

Offers both GUI and CLI access

GUI for intuitive visual flows and Python SDK for advanced automation and customization.

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

Start Integration

netspresso@nota.ai

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