Models and AI packages

Start from a model that is ready to understand, compare, and deploy.

Model pages connect architecture, ONNX graphs, inputs, training details, accuracy, licenses, API usage, deployment targets, and compatible community hardware implementations.

Vision

Classification, object detection, segmentation, tracking, and video understanding.

YOLOMobileNetUNet

Language and embeddings

Text generation, embeddings, retrieval, classification, and private assistants.

Compact LLMBERTEmbedding

Agents and multimodal

Tool-using systems that combine language, vision, data, and application workflows.

Vision agentRAGTool calling

Sensor and edge AI

Audio, anomaly detection, time series, control, and continuous on-device learning.

AudioAnomalySNN

Use a model without knowing the accelerator.

A product developer can deploy a model through a normal API. An advanced user can inspect ONNX, select precision, compare accelerator implementations, target a board, or prepare a custom compiler path.

Use AI Cloud
One model, several paths
1Deploy as managed inference API
2Add to a complete Web AI App
3Run on your own embedded system
4Match with community accelerator implementations
5Target an embedded accelerator