🌐 Website • 📖 Documentation

RunMat is a modern, high-performance runtime for MATLAB® and GNU Octave code that eliminates license fees, vendor lock-in, and performance bottlenecks. Built from the ground up in Rust with a V8-inspired architecture, it delivers:

• 🚀 150-180x faster execution than Octave through JIT compilation
• ⚡ Instant startup (5ms vs 900ms+ in Octave) via advanced snapshotting
• 🎨 GPU-accelerated plotting that's beautiful and responsive
• 📊 Native Jupyter support with rich interactive widgets
• 🛡️ Memory safety and zero crashes guaranteed by Rust
• 💰 $0 licensing costs - completely free and open source

Benchmarks run on Apple M2 Max with BLAS/LAPACK optimization. See benchmarks/ for reproducible test scripts and detailed results.

# Quick install (Linux/macOS)
curl -fsSL https://runmat.org/install.sh | sh

# Quick install (Windows PowerShell)
iwr https://runmat.org/install.ps1 | iex

# Or install from crates.io
cargo install runmat --features gui

# Or build from source
git clone https://github.com/runmat-org/runmat.git
cd runmat && cargo build --release --features gui

For BLAS/LAPACK acceleration on Linux, install the system OpenBLAS package before building:

sudo apt-get update && sudo apt-get install -y libopenblas-dev

# Start the interactive REPL
runmat

# Or run an existing .m file
runmat script.m

# Or pipe a script into RunMat
echo "a = 10; b = 20; c = a + b" | runmat

# Register RunMat as a Jupyter kernel
runmat --install-kernel

# Launch JupyterLab with RunMat support
jupyter lab

% Your existing MATLAB code just works
A = [1 2 3; 4 5 6; 7 8 9];
B = A' * A;
eigenvals = eig(B);
plot(eigenvals);

% Matrix operations that fly - 150x+ faster than Octave
n = 1000;
A = randn(n, n);
B = randn(n, n);
tic; C = A * B; toc  % Executes in ~5ms vs 800ms+ in Octave

% Create a stunning 3D surface plot
[X, Y] = meshgrid(-2:0.1:2, -2:0.1:2);
Z = X .* exp(-X.^2 - Y.^2);
surf(X, Y, Z);

RunMat's tiered execution engine delivers both fast startup and blazing runtime performance.

runmat> .info
🦀 RunMat v0.1.0 - High-Performance MATLAB Runtime
⚡ JIT: Cranelift (optimization: speed)
🧠 GC: Generational (heap: 45MB, collections: 12)
🎨 Plotting: GPU-accelerated (wgpu)
📊 Functions loaded: 52 builtins + 0 user-defined

• Rich output formatting with LaTeX math rendering
• Interactive widgets for parameter exploration
• Seamless plotting integration
• Full debugging support with breakpoints

// Adding a new builtin function is trivial
#[runtime_builtin("myfunction")]
fn my_custom_function(x: f64, y: f64) -> f64 {
    x.powf(y) + x.sin()
}

RunMat is more than just software—it's a movement toward open, fast, and accessible scientific computing. We're building the future of numerical programming, and we need your help.

• GitHub Discussions: Share ideas and get help
• Twitter: @dystr_ai for updates and announcements
• Newsletter: Subscribe for monthly updates

RunMat is licensed under the MIT License with Attribution Requirements. This means:

✅ Free for everyone - individuals, academics, most companies
✅ Open source forever - no vendor lock-in or license fees
✅ Commercial use allowed - embed in your products freely
⚠️ Attribution required - credit "RunMat by Dystr" in public distributions
⚠️ Special provisions - large scientific software companies must keep modifications open source

See LICENSE.md for complete terms or visit runmat.org/license for FAQs.

Built with ❤️ by Dystr Inc. and the RunMat community

⭐ Star us on GitHub if RunMat helps your work!

🚀 Get Started • 🐦 Follow @dystr

MATLAB® is a registered trademark of The MathWorks, Inc. RunMat is not affiliated with, endorsed by, or sponsored by The MathWorks, Inc.