TAO Toolkit 3.0-21.08

  • New pretrained models and training for computer vision:
  • Body Pose estimation
  • Emotion recognition
  • Facial landmark
  • License plate detection and recognition
  • Heart rate estimation
  • Gesture recognition
  • Gaze estimation
  • People segmentation
  • Introducing ASR and NLP models with inference samples for:
  • Speech to Text
  • Named Entity Recognition (NER)
  • Question/Answering
  • Punctuation
  • Text classification
  • Turnkey training support on AWS, GCP and Azure.
  • TAO Toolkit 3.0 brings support for NVIDIA Ampere GPUs with third generation tensor core additions and various performance optimizations
  • Improved PeopleNet model to detect difficult scenarios such as people sitting down, rotated/ warped objects
  • Train with popular networks: EfficientNet, ResNet, YOLOV3/V4, FasterRCNN, SSD, DetectNet_v2, MaskRCNN and UNET
  • Out of the box deployment on NVIDIA Triton and DeepStream SDK for vision AI and Riva for conversational AI
  • Enable faster training with jobs split up across multi-GPUs
Operating System
  • Ubuntu 18.04
  • Driver version >= 455
  • Docker-ce > 19.03
  • Nvidia-docker2
  • Docker-API 1.40

Latest Product News


Developer Tutorial

Learn how to create highly optimized production quality pose estimation model.


Supercharge Your Workflows With Transfer Learning

Learn how NVIDIA TAO Toolkit and Pretrained Models can transform your development efforts.

Read Whitepaper
number plate detection

Developer Tutorial

Learn how to create a real-time number plate detection and recognition app.

Read Blog
conversation AI models

Developer Tutorial

Learn how to build and deploy conversational AI models using the NVIDIA TAO Toolkit.

Read Blog

Getting Started Resources

Install TAO Toolkit launcher Python package

Conversational AI

Vision AI

Platform Compute Download
x86 + GPU CUDA 10.2 / cuDNN 8.0 / TensorRT 7.1 Download
x86 + GPU CUDA 10.2 / cuDNN 8.0 / TensorRT 7.2 Download
x86 + GPU CUDA 11.0 / cuDNN 8.0 / TensorRT 7.1 Download
x86 + GPU CUDA 11.0 / cuDNN 8.0 / TensorRT 7.2 Download
x86 + GPU CUDA 11.1 / cuDNN 8.0 / TensorRT 7.2 Download
x86 + GPU CUDA 11.3 / cuDNN 8.1 / TensorRT 8.0 Download
Jetson Jetpack 4.4 Download
Jetson Jetpack 4.5 Download
Jetson Jetpack 4.6 Download
Clara AGX CUDA 11.1 / CuDNN 8.0.5 / TensorRT 7.2.2 Download


Developer Forums

Success Stories

Blogs & Tutorials

Community Projects

  • Take a look at our innovative developer community projects and submit your cool project to be featured on our community project hub


Free Self-Paced DLI Online Courses

  • Learn how to build end-to-end intelligent video analytics pipelines using DeepStream and Jetson Nano >> Enroll now
  • Learn how to get started with AI using Jetson Nano >> Enroll now

Ethical AI

NVIDIA’s platforms and application frameworks enable developers to build a wide array of AI applications. Consider potential algorithmic bias when choosing or creating the models being deployed. Work with the model’s developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended.