System requirements

Mojo runs on Mac, Linux, and Windows (with WSL). You don't need a GPU to program with Mojo---GPU support is optional.

For installation instructions, see the install guide.

Operating system

Linux

• Ubuntu 22.04 LTS or later
• x86-64 CPU (with SSE4.2 or newer) or ARM64 (AWS Graviton2/3)
• glibc 2.34 or later

Mojo is expected to work on other Linux distributions that meet the glibc requirement, but we only test on Ubuntu. If your system has an older glibc version, run Mojo inside a container with a compatible base image such as Ubuntu 22.04.

Mac

• macOS Sequoia (15) or later
• Apple silicon (M1--M5 processor)

Windows

Mojo doesn't natively support Windows. You can use Mojo on Windows with WSL using a compatible version of Ubuntu (see the Linux requirements).

Hardware

• CPU: x86-64 (Intel/AMD with SSE4.2) or ARM64 on Linux; Apple silicon on macOS
• RAM: 8 GB minimum
• GPU: Optional. Mojo supports GPU programming across NVIDIA, AMD, and Apple silicon. See GPU compatibility below for supported hardware and driver requirements.

Software

• Python 3.10--3.14
• C++ compiler (g++ or clang++) on Linux
• Xcode or Xcode Command Line Tools 16 or later on macOS

GPU compatibility

Mojo supports GPU programming across NVIDIA, AMD, and Apple silicon GPUs. This section covers which GPUs work with Mojo and the software each vendor requires.

We categorize GPU compatibility into two levels:

• Continuously tested: Run in Modular's CI on every release. High confidence that GPU code compiles and executes correctly.
• Known compatible: Confirmed to work by Modular or community members, but not continuously tested. These GPUs share an architecture with a tested GPU and should work without issues.

NVIDIA GPUs

Software requirements

• NVIDIA GPU driver 580 or later

  Check your driver version with nvidia-smi. To update, see the NVIDIA driver docs.

• Older drivers: If you're using an NVIDIA driver older than 580 (common on some cloud providers), set the MODULAR_NVPTX_COMPILER_PATH environment variable to point to a system ptxas binary from a CUDA Toolkit installation:

  export MODULAR_NVPTX_COMPILER_PATH=/usr/local/cuda/bin/ptxas

  This bypasses the bundled compiler's driver version check and enables Mojo to compile GPU code with your existing driver.

Hardware compatibility

GPU	Architecture	Arch target
Continuously tested
B200	Blackwell	sm_100
H100	Hopper	sm_90
Known compatible
B300	Blackwell	sm_103
B100	Blackwell	sm_100
DGX Spark	Blackwell	sm_121
H200	Hopper	sm_90
L4	Ada Lovelace	sm_89
L40	Ada Lovelace	sm_89
RTX 50XX series	Blackwell	sm_120
RTX 40XX series	Ada Lovelace	sm_89
A100	Ampere	sm_80
A10	Ampere	sm_86
RTX 30XX series	Ampere	sm_86
Jetson Orin / Orin Nano	Ampere	sm_87
Jetson Thor	Blackwell	sm_110
RTX 20XX series	Turing	sm_75

Pre-Turing NVIDIA GPUs: Pre-Turing GPUs (such as Pascal-generation GTX 10XX and Tesla P100) are not supported out of the box. To use Mojo on these GPUs, set the MODULAR_NVPTX_COMPILER_PATH environment variable to point to a system ptxas binary compatible with your hardware and driver version.

AMD GPUs

Software requirements

• AMD GPU driver 6.3.3 or later (MI355X requires ROCm 7.0 or later)

  • For data center GPUs (Instinct series), see the Ubuntu native install guide.
  • For Radeon GPUs on Ubuntu, see the Linux install guide for Radeon software.
  • For Radeon GPUs on WSL, see the WSL install guide for Radeon software.

Hardware compatibility

GPU	Architecture	Arch target
Continuously tested
MI355X	CDNA4	gfx950
MI300X	CDNA3	gfx942
Known compatible
MI325X	CDNA3	gfx942
MI250X	CDNA2	gfx90a
Radeon RX 9070	RDNA4	gfx1201
Radeon RX 9060	RDNA4	gfx1200
Radeon 880M	RDNA3.5	gfx1150
Radeon 860M	RDNA3.5	gfx1152
Radeon 8060S	RDNA3.5	gfx1151
Radeon RX 7900	RDNA3	gfx1100
Radeon RX 7800 / 7700	RDNA3	gfx1101
Radeon RX 7600	RDNA3	gfx1102
Radeon 780M	RDNA3	gfx1103

Apple silicon GPUs

Software requirements

• macOS Sequoia (15) or later

• Xcode 16 or later

• You may need to install the Metal toolchain after upgrading macOS or Xcode:

  xcodebuild -downloadComponent MetalToolchain

Hardware compatibility

Chip	Support level
M5	Known compatible
M4	Known compatible
M3	Known compatible
M2	Known compatible
M1	Known compatible

Troubleshooting GPU detection

What Mojo looks for

When Mojo needs a GPU, the runtime attempts to load vendor-specific driver libraries in this order:

1. NVIDIA (CUDA): loads libcuda.so.1 and libnvidia-ml.so.1
2. AMD (HIP): loads libamdhip64.so
3. Apple (Metal): uses the Metal framework (built into macOS)

If Mojo can't load any of these libraries, it falls back to CPU execution.

Verifying GPU access

Use the --target-accelerator flag to compile for a specific GPU architecture:

mojo build --target-accelerator=sm_90 my_kernel.mojo

To check that your system's GPU is accessible at runtime, try a minimal GPU program:

check_gpu.mojo

from gpu.host import DeviceContext

def main():
    var ctx = DeviceContext()
    print("GPU:", ctx.name())

mojo check_gpu.mojo

If Mojo can't find a GPU, this raises an error explaining what it tried.

Common issues

GPU not detected despite nvidia-smi showing a GPU:

• Verify that the NVIDIA driver version is 580 or later (nvidia-smi shows the version in the top-right corner). If your driver is older, set MODULAR_NVPTX_COMPILER_PATH as described in the NVIDIA software requirements section above.
• Ensure libcuda.so.1 is on your library path. On most systems, the NVIDIA driver installer places it in /usr/lib/x86_64-linux-gnu/ or /usr/lib64/.
• If using a container, make sure you're passing GPU access through (for example, docker run --gpus all).
• Set MLRT_CUDA_DEBUG=1 to get detailed logging of the CUDA detection process.

AMD GPU not detected:

• Verify that you have ROCm/HIP installed and that libamdhip64.so is available.
• Check your ROCm version: apt show rocm-libs 2>/dev/null | grep Version or rocm-smi --showdriverversion.
• Ensure your user is in the render and video groups: sudo usermod -aG render,video $USER (then log out and back in).

Apple GPU not detected or Metal toolchain errors:

• Ensure you're on macOS Sequoia (15) or later: sw_vers.
• Install the Metal toolchain: xcodebuild -downloadComponent MetalToolchain.
• Verify that you have Xcode Command Line Tools: xcode-select --install.

Pre-Turing NVIDIA GPU errors:

• Set MODULAR_NVPTX_COMPILER_PATH to a compatible system ptxas binary. For example: export MODULAR_NVPTX_COMPILER_PATH=/usr/local/cuda/bin/ptxas.

WSL: GPU not detected or driver mismatch:

• Make sure you follow the WSL-specific installation instructions for your GPU vendor, not the native Linux instructions.
• For NVIDIA on WSL, the GPU driver should be installed on the Windows host, not inside WSL. WSL automatically makes the host driver available.
• For AMD on WSL, see the WSL install guide for Radeon software.

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If your GPU works with Mojo but isn't listed here, let us know on the Modular community forum or file a GitHub issue.