CentiLeo vs Mitsuba 3
CentiLeo
centileo.comMitsuba 3
mitsuba-renderer.orgSide by side
| Figure | CentiLeo | Mitsuba 3 |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · 3D Rendering Software | 7.1 (#31) | 8.4 (#5) |
| Integrations | The 3ds Max 0.660 release notes list material converters for selected 3ds Max, Corona and FStorm shaders. | The documentation includes a tutorial on interoperability between PyTorch and Mitsuba. |
| Limits | The features page lists Windows, 3ds Max and Cinema 4D only, and NVIDIA GPUs with compute capability 3.0 or higher; it says GPUs with at least 3 GB device memory are required, though 2 GB GPUs may also work. | The Python package includes thirteen variants by default; additional variants require compiling a custom version of Dr.Jit using CMake. |
| System requirements | The download page lists Windows 7–11, at least 12 GB RAM and an NVIDIA GPU with at least 4 GB VRAM for both supported host applications. | Installation requires Python 3.10 or later; GPU computation optionally requires NVIDIA driver 535 or later, and parallel CPU computation optionally requires LLVM 18 or later. |
Plans
In their own words
Mitsuba 3
Mitsuba 3 is a free, open-source, research-oriented system for forward and inverse light-transport simulation. It offers monochrome, RGB, and spectral rendering with optional polarization tracking, and computes derivatives with respect to camera pose, geometry, materials, textures, and volumes. Dr.Jit compiles rendering code for CPUs through LLVM and NVIDIA GPUs through CUDA and OptiX. Python integration supports development of materials, textures, and rendering algorithms, with documentation covering PyTorch interoperability. Installation is recommended through pip and requires Python 3.10 or later. Optional GPU computation requires NVIDIA driver 535 or later; parallel CPU computation optionally requires LLVM 18 or later. The project reports Linux x86_64, macOS aarch64 and x86_64, and Windows x86_64 support. Its plugins cover materials, light sources, and complete rendering algorithms. The Python package includes thirteen variants by default; more require compiling a custom Dr.Jit version with CMake. Tutorials, notebooks, how-to guides, and API and plugin references are provided.