Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.


layout: forward target: https://developers.google.com/mediapipe title: Home nav_order: 1


Attention: We have moved to https://developers.google.com/mediapipe as the primary developer documentation site for MediaPipe as of April 3, 2023.

MediaPipe

Attention: MediaPipe Solutions Preview is an early release. Learn more.

On-device machine learning for everyone

Delight your customers with innovative machine learning features. MediaPipe contains everything that you need to customize and deploy to mobile (Android, iOS), web, desktop, edge devices, and IoT, effortlessly.

Get started

You can get started with MediaPipe Solutions by by checking out any of the developer guides for vision, text, and audio tasks. If you need help setting up a development environment for use with MediaPipe Tasks, check out the setup guides for Android, web apps, and Python.

Solutions

MediaPipe Solutions provides a suite of libraries and tools for you to quickly apply artificial intelligence (AI) and machine learning (ML) techniques in your applications. You can plug these solutions into your applications immediately, customize them to your needs, and use them across multiple development platforms. MediaPipe Solutions is part of the MediaPipe open source project, so you can further customize the solutions code to meet your application needs.

These libraries and resources provide the core functionality for each MediaPipe Solution:

  • MediaPipe Tasks: Cross-platform APIs and libraries for deploying solutions. Learn more.
  • MediaPipe models: Pre-trained, ready-to-run models for use with each solution.

These tools let you customize and evaluate solutions:

  • MediaPipe Model Maker: Customize models for solutions with your data. Learn more.
  • MediaPipe Studio: Visualize, evaluate, and benchmark solutions in your browser. Learn more.

Legacy solutions

We have ended support for these MediaPipe Legacy Solutions as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to a new MediaPipe Solution. See the Solutions guide for details. The code repository and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be provided on an as-is basis.

For more on the legacy solutions, see the documentation.

Framework

To start using MediaPipe Framework, install MediaPipe Framework and start building example applications in C++, Android, and iOS.

MediaPipe Framework is the low-level component used to build efficient on-device machine learning pipelines, similar to the premade MediaPipe Solutions.

Before using MediaPipe Framework, familiarize yourself with the following key Framework concepts:

Community

  • Slack community for MediaPipe users.
  • Discuss - General community discussion around MediaPipe.
  • Awesome MediaPipe - A curated list of awesome MediaPipe related frameworks, libraries and software.

Contributing

We welcome contributions. Please follow these guidelines.

We use GitHub issues for tracking requests and bugs. Please post questions to the MediaPipe Stack Overflow with a mediapipe tag.

Privacy Notice

Last modified: June 5, 2026

When you use MediaPipe Tasks, processing of the input data (e.g. images, video, text) takes place on device, and MediaPipe does not send that input data to Google servers. As a result, you can use our MediaPipe Tasks APIs for processing data that should not leave the device.

MediaPipe Tasks APIs send metrics about the performance and utilization of the APIs in your app to Google. Google uses this metrics data to measure performance, usage, debug, maintain and improve the MediaPipe Tasks, as further described in our Privacy Policy.

You are responsible for obtaining informed consent from your app users about Google's processing of MediaPipe metrics data as required by applicable law.

Resources

Publications

Videos

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

mediapipe_nightly-1.0.1rc20260825-py3-none-win_arm64.whl (18.0 MB view details)

Uploaded Python 3Windows ARM64

mediapipe_nightly-1.0.1rc20260825-py3-none-win_amd64.whl (20.4 MB view details)

Uploaded Python 3Windows x86-64

mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_x86_64.whl (38.1 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_aarch64.whl (36.0 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

mediapipe_nightly-1.0.1rc20260825-py3-none-macosx_11_0_arm64.whl (39.7 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

File details

Details for the file mediapipe_nightly-1.0.1rc20260825-py3-none-win_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.1rc20260825-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 9342a61ab6daf5b4cea1846fc6c0988d6ea3008f4ab63eaea7575100a3f41184
MD5 27805d387b4d802a84677a637fad8af7
BLAKE2b-256 16b999dcd83a708f0940429dd62f1d9096311239b7494277d39e5f65fa5e3e5e

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.1rc20260825-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.1rc20260825-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 765e83cedcfc16a021a729a68a5bdc7f4ebf5ae6ad72f52969e2398a10e9daa7
MD5 5253a9e0f0c3d0855e2e2d5af9fc828f
BLAKE2b-256 6cc5bd654b03a00e3510757aef01bdf64bdca1cd064b21210ede53bca134fc34

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2e2a6cf444c884ca4a02e17ed77b90516a3c0e4f59cdba405bae39da4d71547d
MD5 146e91f91c63ab90ee8454e859ce0568
BLAKE2b-256 2ca68630cdf9052b2b85cb2334765dc82ab190ab509e0966391e67e32148a4d2

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.1rc20260825-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 d269ff129b9bdc3b78cf2d11ebef7d6d7dbd1696a02d96adb14a58d5c9f37e61
MD5 cb6a1fabb2b70934879fd019531dec4f
BLAKE2b-256 bca99e216fa080530508c83d020e84d0eb5828decea13f454db3d2672651db7b

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.1rc20260825-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.1rc20260825-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6baf4ddaddbaae99f797a638b419d520fad189ab91f798c1b311b6d7449e1239
MD5 43c23c1717f9076739c71c56f44c94c2
BLAKE2b-256 ed7ef09d4dbb2cc7418f5191c1bff6a846c6d8655ea9e5b347ef1c2c04731452

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

1.0.1rc20260825 This release

5 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page