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tensorflow/mesh

Mesh TensorFlow: Model Parallelism Made Easier

GraphCanon updated 2w · GitHub synced 2w

1.6k stars255 forksLast push 2y Python Apache-2.0

Decision brief

Mesh TensorFlow supports simplified model parallelism across multiple devices in Python under the Apache-2.0 license.

Good fit when

  • When working on large models that benefit from being split across many devices.
  • For developers already using TensorFlow who need to easily manage model parallelism.

Avoid when

  • If you are looking for a tool that simplifies other aspects of machine learning beyond model-parallel computation.
  • For projects with limited GPU/TPU resources where multi-device parallelism is not required.

Observed Jul 12, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Archived (993d since push)
As of 2w
Provenance
Not a fork · Organization account
As of 2w
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install mesh
PyPI

How it fits your stack(1)

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Relationship graph

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Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A library from the TensorFlow ecosystem designed for simplifying model parallelism across multiple devices.

Capability facts

Languages
python

Source: github.language · Aug 7, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 7, 2026)

pip install mesh-tensorflow
Source link

Tags

README

Installation

To install the latest stable version, run

pip install mesh-tensorflow

To install the latest development version, run

pip install -e "git+https://github.com/tensorflow/mesh.git#egg=mesh-tensorflow"

Installing mesh-tensorflow does not automatically install or update TensorFlow. We recommend installing it via pip install tensorflow or pip install tensorflow-gpu. See TensorFlow’s installation instructions for details. If you're using a development version of Mesh TensorFlow, you may need to use TensorFlow's nightly package (tf-nightly).

For agents

This page has a .md twin and JSON over the API.

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