A computer that matches or exceeds the following requirements will run GibbsCAM very comfortably. Please note that the larger or more complex your parts are, the more GibbsCAM will demand from your system.


Recommended System

  • Windows 10 Or Windows 11 (with all available Windows updates).
  • Intel: Core i9 or i7 with four or more cores or AMD: Ryzen or Threadripper.
  • 16 GB RAM (more is recommended for very complex parts).
  • A quality Nvidia with 4+GB of video memory with the latest drivers installed.
  • 2 GB of available hard drive space (for virtual memory usage and temporary file storage).


Cards to avoid:

Intel video cards

SiS chipset cards

3D Labs video cards

other high-end "CAD" cards


Low-end cards should especially be avoided. The integrated Intel video chipset runs GibbsCAM particularly poorly. This video card is often included in less expensive systems.


SLI Mode - Running newer systems in SLI mode with GibbsCAM can result in poor performance and is not recommended.


Nvidia vs. AMD graphics cards:

We don't have specific video cards that we recommend.  However, historically we have encountered less issues with Nvidia cards than we have with AMD cards.


GibbsCAM is very graphics intensive and heavily uses the video card.  If you are looking to build the optimal machine for running GibbsCAM, you will definitely want to get as good of a video card as you can get.  Either a quality GeForce or Quadro card will be sufficient to run GibbsCAM, but more powerful cards will perform better so it will depend on how much you are willing to spend vs the power it provides.


Core Speed vs. Number of Cores:

For toolpath creation typically only a single core can be utilized for a given operation. This is because for toolpath generation, it needs to know where it has been before it can calculate any further and separate cores would not be able to know this. Multiple cores can be used when calculating multiple unrelated toolpaths at the same time that do not require knowledge of previous operations that are currently being calculated (such as when using material only).  This puts a higher emphasis on core speed over number of cores.