We recommend to use Linux operating systems to run Smuthi. Otherwise, Smuthi can run on Windows, too, but issues regarding dependencies or performance are more likely.

Installing Smuthi under Windows


First make sure that a 64 Bit Python 3.6 or newer is installed on your computer. You can install for example Anaconda or WinPython to get a full Python environment.


Anaconda users are required to update numpy to the latest version from conda-forge before intalling Smuthi. It is also recommended to create a dedicated conda environment for the Smuthi installation. In case the environment gets messed up by destructive interference between Pip and conda, the main Anaconda installation is then still unaffected.


Open a command window and type:

python -m pip install smuthi

Depending on where pip will install the package, you might need administrator rights for that.

Alternatively, install locally from source (see below section Installing Smuthi from source).

Installing Smuthi from source

This option allows to install a non-release version of Smuthi or to modify the source code and then run your custom version of Smuthi.


Clone Smuthi and install it locally by:

git clone
cd smuthi/
sudo python3 -m pip install -e .


Local installation requires a Fortran compiler. Visit the MinGW getting started page and follow the instructions to install gfortran. Make sure to add the bin folder of your MinGW installation to the Windows PATH variable. See Environment Settings section of the MinGW getting started page for instructions.


The MinGW version needs to fit to your Python installation. If you have 64 Bit Python, make sure to download a Mingw-64

Then, download or git clone the Smuthi project folder from the gitlab repository. Open a command prompt and change directory to the Smuthi project folder and enter:

python -m pip install -e .

If that command fails (e.g. because pip tries to compile the extension modules with the MSVC compiler instead of mingw), you can try:

python -m pip install wheel
python -m pip install numpy
python develop

Depending on the Python version, the above commands may fail to create statically linked extensions. This will lead to runtime errors saying that some DLL cannot be found. In that case you can try to overwrite the extension modules statically linked PYD-files by running the command:

python build_ext --inplace --compiler=mingw32 --fcompiler=gnu95 -f

Installing Smuthi from source on Windows can be troublesome. If you experience difficulties, please seek support from the Smuthi mailing list or open an issue on the Smuthi GitLab repository.


After installation from source you can check the unit tests:


sudo python3 -m pip install nose2


python -m pip install nose2

GPU-acceleration (optional)


PyCuda support is recommended if you run heavy simulations with many particles. In addition, it can speed up certain post processing steps like the evaluation of the electric field on a grid of points, e.g. when you create images of the field distribution. For simple simiulations involving one particle on a substrate, you might well go without.

If you want to benefit from fast simulations on the GPU, you need:

Under Ubuntu, install PyCuda simply by:

sudo python3 -m pip install pycuda

Under Windows, installing PyCuda this is not as straightforward as under Linux. There exist prebuilt binaries on Christoph Gohlke’s homepage. See for example these instructions for the necessary steps to get it running.


Windows: Unable to import the nfmds module

Try to install Smuthi from source.