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 CloudOne 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