# openvinotoolkit/open_model_zoo

Pre-trained Deep Learning models and demos (high quality and extremely fast)

Repository: https://github.com/openvinotoolkit/open_model_zoo
Canonical: https://ross.abutalabs.com/products/open_model_zoo
Homepage: https://docs.openvino.ai/latest/model_zoo.html
Language: Python
License: Apache-2.0
License Family: permissive
Topics: models, caffemodel, demo, tensorflow-models, model-zoo, model, deep-learning-models, cnn-model, openvino, inference, onnx-models, pytorch-models, openvino-model-zoo, openvino-models, openvino-toolkit
Last push: 2026-08-24T07:28:55+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2879, "days_push": 9, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4420, forks 1407 (observed 2026-08-28T04:08:48.741034+00:00)

## What it is
A collection of pre-trained deep learning models (Intel and public) plus demos and tools for use with the OpenVINO inference toolkit. It includes a model downloader, accuracy checker, and sample applications for high-performance inference.

## Use cases
- download pre-trained models for OpenVINO inference
- run object detection demos with optimized models
- validate model accuracy with accuracy checker
- find fast pre-trained CNN models instead of training my own
- deploy deep learning inference on Intel hardware
- convert and benchmark public models like ONNX or TensorFlow

## When to choose
- you use OpenVINO and need ready-made optimized models
- you want fast inference demos for vision tasks on Intel CPUs/GPUs
- you need a model downloader and accuracy validation tooling

## When to avoid
- you need new models - the repo is in maintenance mode
- you train models rather than run inference
- you target non-Intel runtimes like CUDA-only pipelines

## Facets
- artifact type: dataset
- maturity: maintenance
- function: machine-learning, deep-learning, computer-vision, image-processing, llm-inference
- domain: deep-learning, computer-vision, machine-learning, artificial-intelligence
- platform: python, cross-platform, windows
- tags: openvino, pre-trained-models, model-zoo, inference, model-downloader, demos, intel, gpu, linux, macos

## Member repositories
- openvinotoolkit/open_model_zoo (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:48.741034+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:20:59.422214+00:00, confidence not recorded.
  - readme: https://github.com/openvinotoolkit/open_model_zoo (fetched 2026-08-28T04:08:48.741034+00:00, sha 0e837f3ca1b1)
  - homepage: https://docs.openvino.ai/latest/model_zoo.html (fetched 2026-08-29T09:08:35.793173+00:00, sha 89d2bb60492c)
- Data as of 2026-08-30T08:39:29.467469+00:00.