Packages

All the Modular APIs and tools (including MAX and Mojo) are included in a single Python/Conda package named modular. This page explains what's in the package and shows how to install it.

If you just want to get started with Modular, instead see our quickstart guide.

Package managers

You can install modular as a Python or Conda package. The install instructions below include commands for popular package managers such as pixi, uv, pip, and conda, but you can also use something else.

Traditional tools like pip and conda might be necessary for existing production environments or Docker containers, but for your local development, we recommend using Pixi.

Pixi is both a package manager and virtual environment manager, which alone makes development a lot easier, but it's also language agnostic, extremely fast, and includes lock files to easily reproduce your project environment.

You'll notice that our GitHub code examples include a pixi.toml file. This file configures the environment to make sure we all use the same packages and get the same results—you just need to install pixi.

So if you're not set on using a particular package manager, we suggest you try pixi. If you haven't used it before, check out our Pixi basics guide or the official Pixi docs.

Install

To get the latest improvements and new features, we recommend installing our nightly build, which we release several times a week. If you want a better tested but older version, you can install a stable build. (Each release is described in the changelog.)

System requirements:

Mac

Linux

WSL

We recommend installing with pixi for the most reliable experience.

pixi

1. If you don't have it, install pixi:

   curl -fsSL https://pixi.sh/install.sh | sh

   Then restart your terminal for the changes to take effect.

2. Create a project:

   pixi init example-project \
     -c https://conda.modular.com/max-nightly/ -c conda-forge \
     && cd example-project

   Tip: You can skip the -c options if you add these channels as defaults.

3. Install modular (nightlyTo get the stable build, change the version in the website header.):

   pixi add modular

4. Start the virtual environment:

   pixi shell

uv

1. If you don't have it, install uv:

   curl -LsSf https://astral.sh/uv/install.sh | sh

   Then restart your terminal to make uv accessible.

2. Create a project:

   uv init example-project && cd example-project

3. Create and start a virtual environment:

   uv venv && source .venv/bin/activate

4. Install modular (nightlyTo get the stable build, change the version in the website header.):

   uv pip install modular \
       --index https://whl.modular.com/nightly/simple/ \
       --prerelease allow

The modular package installs MAX, Mojo, and other package dependencies.

GitHub stable branch

If you're using a stable build and want to clone the Modular repo, make sure you checkout the stable branch (because the main branch includes the latest nightly code). For example:

git clone -b stable https://github.com/modular/modular.git

Uninstall

pixi

You can uninstall modular from your virtual environment with this command:

pixi remove modular

To deactivate your virtual environment, run:

exit

uv

You can uninstall modular from your virtual environment with the following command:

uv pip uninstall modular

To deactivate your virtual environment, run:

deactivate

pip

You can uninstall modular from your virtual environment with the following command:

pip uninstall modular

To deactivate your virtual environment, run:

deactivate

conda

You can uninstall modular from your virtual environment with this command:

conda remove modular

To deactivate your virtual environment, run:

deactivate

What's included

Here's a summary of what's in the modular package.

conda/pixi

The modular Conda package installs the following:

• MAX tools and libraries:
  • max CLI
  • max Python library
  • max Mojo library
  • MAX Engine C API
• The mojo package:
  • mojo CLI (includes the Mojo compiler)
  • Mojo standard library
  • Mojo language server (LSP) for IDE/editor integration
  • Mojo debugger (includes LLDB)
  • Mojo code formatter
  • Mojo REPL

pixi known issues:

• You might encounter issues if you invoke pixi within a conda virtual environment. It's best if you don't mix the two tools.

pip/uv

The modular Python wheel installs the following:

• MAX tools and libraries:
  • max CLI
  • max Python library
  • max Mojo library
• The mojo package:
  • mojo CLI (includes the Mojo compiler)
  • Mojo standard library
  • Mojo language server (LSP) for IDE/editor integration
  • Mojo debugger (includes LLDB)
  • Mojo code formatter
  • Mojo REPL

Note

For information about the mojo package, see the Mojo install guide.

System requirements

To install modular, your system must meet these specifications.

Mac

• macOS Sequoia (15) or later
• Apple silicon (M1 - M5 processor)
• Python 3.10 - 3.14
• Xcode or Xcode Command Line Tools 16 or later
• Apple silicon GPU support is available for Mojo GPU programming. See GPU compatibility for details. You may need to run xcodebuild -downloadComponent MetalToolchain to install the Metal utilities required for GPU programming.

Linux

• Ubuntu 22.04 LTS
• x86-64 CPU (with SSE4.2 or newer) or AWS Graviton2/3 CPU
• Minimum 8 GiB RAM (or much more, depending on the model you run)
• Python 3.10 - 3.14
• g++ or clang++ C++ compiler
• To use GPUs, see the GPU compatibility

Windows

Windows is not officially supported at this time.

In the meantime, you can try MAX on Windows with WSL, using a compatible version of Ubuntu (see our requirements for Linux).

GPU compatibility

MAX supports both CPUs and GPUs, so you don't always need a GPU to serve a model. But if you want to accelerate inference with GPUs or program for GPUs with Mojo, the following GPUs are compatible.

NVIDIA GPUs

GPU	Architecture
Tested for serving
B200	Blackwell
H100	Hopper
H200	Hopper
Known compatible for development
B300	Blackwell
B100	Blackwell
L4	Ada Lovelace
L40	Ada Lovelace
A100	Ampere
A10	Ampere
RTX 50XX series	Blackwell
RTX 40XX series	Ada Lovelace
RTX 30XX series	Ampere
Jetson Orin / Orin Nano	Ampere

Software requirement: NVIDIA GPU driver 580 or later. Check your version with nvidia-smi. To update, see the NVIDIA driver docs. If your driver is older than 580, set the MODULAR_NVPTX_COMPILER_PATH environment variable to a system ptxas binary (for example, export MODULAR_NVPTX_COMPILER_PATH=/usr/local/cuda/bin/ptxas).

AMD GPUs

GPU	Architecture
Tested for serving
MI355X	CDNA4
MI300X	CDNA3
MI325X	CDNA3
Known compatible for development
MI250X	CDNA2
Radeon RX 9070	RDNA4
Radeon RX 9060	RDNA4
Radeon 880M	RDNA3.5
Radeon 860M	RDNA3.5
Radeon 8060S	RDNA3.5
Radeon RX 7900	RDNA3
Radeon RX 7800 / 7700	RDNA3
Radeon RX 7600	RDNA3

Software requirement: AMD GPU driver 6.3.3 or later (MI355X requires ROCm 7.0 or later). For installation, see the Ubuntu native install guide.

Apple silicon GPUs

Apple silicon GPU support (M1--M5) is functional for GPU programming with Mojo. Large GenAI model inference via MAX isn't yet available on Apple silicon. For details, see the Mojo system requirements.

Notes

• Many GPUs are available in variants with different amounts of memory, and each AI model has different memory requirements. Even if your GPU architecture is listed as compatible, confirm that the available memory is sufficient for the model you're using.

• MAX can serve models on either CPU or GPU, but some models require one or more GPUs. When you browse our supported models, you can check for multi-GPU support.

• For comprehensive GPU hardware tables, arch targets, and troubleshooting, see the Mojo system requirements page.

• To deploy MAX in containers, see the deployment guide.

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