NumPy vs. RunMat Comparison


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About Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.	About RunMat (by Dystr) is a fast, free, open-source alternative for running MATLAB code. Users can run their existing .m files with complete MATLAB language grammar and core semantics. No license fees, no lock-in. 300+ built-in functions supported. RunMat is built with a modern Rust runtime featuring a tiered execution model: an interpreter (Ignition) for instant 5ms startup and a JIT compiler (Turbine/Cranelift) for hot paths. GPU acceleration is automatic via a fusion engine that detects elementwise operation chains and dispatches them as optimized GPU kernels across NVIDIA, AMD, Apple Silicon, and Intel GPUs through Metal, DirectX 12, Vulkan, and WebGPU. Up to 131x faster than NumPy and 7x faster than PyTorch on dense numerical workloads. Runs everywhere: CLI, NPM package, Homebrew, Jupyter kernel, or instantly in the browser via WebAssembly + WebGPU. Single portable binary. MIT licensed.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Component Library solution for DevOps teams	Audience Engineers, Scientists, Researchers
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing $0 Free, Open Source. MIT licensed runtime with no seat limits. Cloud plans available for collaboration and team features. Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information NumPy numpy.org	Company Information RunMat Founded: 2022 United States runmat.com
Alternatives Polars	Alternatives Rio Terminal
h5py HDF5	MATLAB The MathWorks
broot	Google Cloud Deep Learning VM Image Google
PyQtGraph	TypeGPU Software Mansion
Dask View All	YAKINDU Model Viewer itemis AG View All
Categories Component Libraries Supported	Categories Computer-Aided Engineering (CAE) Supported
	Show More Features Computer-Aided Engineering (CAE) Features CAD/CAM Compatibility Not Supported Finite Element Analysis Not Supported Fluid Dynamics Supported Import / Export Files Supported Integrated 3D Modeling Not Supported Manufacturing Process Simulation Supported Mechanical Event Simulation Supported Multibody Dynamics Not Supported Thermal Analysis Supported
Integrations 3LC Supported Codédex Supported Coiled Supported Cython Supported Dash Supported Flower Supported JAX Supported Jupyter Notebook Not Supported MPI for Python (mpi4py) Supported PaizaCloud Supported PyCharm Supported Spyder Supported Train in Data Supported Unify AI Supported Visual Studio Code Supported Yamak.ai Supported Yandex Data Proc Supported imageio Supported npm Not Supported scikit-learn Supported Show More Integrations View All 22 Integrations	Integrations 3LC Not Supported Codédex Not Supported Coiled Not Supported Cython Not Supported Dash Not Supported Flower Not Supported JAX Not Supported Jupyter Notebook Supported MPI for Python (mpi4py) Not Supported PaizaCloud Not Supported PyCharm Not Supported Spyder Not Supported Train in Data Not Supported Unify AI Not Supported Visual Studio Code Not Supported Yamak.ai Not Supported Yandex Data Proc Not Supported imageio Not Supported npm Supported scikit-learn Not Supported Show More Integrations View All 4 Integrations
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