miniforge VS conda

Compare miniforge vs conda and see what are their differences.

miniforge

A conda-forge distribution. (by conda-forge)

conda

A system-level, binary package and environment manager running on all major operating systems and platforms. (by conda)
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miniforge conda
56 30
5,078 6,051
6.2% 1.7%
7.7 9.8
5 days ago 1 day ago
Shell Python
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

miniforge

Posts with mentions or reviews of miniforge. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-02.

conda

Posts with mentions or reviews of conda. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-09.

What are some alternatives?

When comparing miniforge and conda you can also consider the following projects:

mamba - The Fast Cross-Platform Package Manager

pyenv - Simple Python version management

Poetry - Python packaging and dependency management made easy

PDM - A modern Python package and dependency manager supporting the latest PEP standards

pip-tools - A set of tools to keep your pinned Python dependencies fresh.

pip - The Python package installer

wheel - Adoption analysis of Python Wheels: https://pythonwheels.com/

PyInstaller - Freeze (package) Python programs into stand-alone executables

rez - An integrated package configuration, build and deployment system for software

tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.