About ALGLIB
Industrial-grade numerical library.
Trusted in research and industry since 1999.
C++ · C# · Java · Python · Delphi
Windows · Linux · generic
x64 · ARM64 · generic
Latest release: 4.07.0, 2025-12-29
Release frequency: 3 releases per year
Licensing: commercial, free
Why choose ALGLIB?
- Easy integration. Single, self-contained library with no mandatory dependencies.
- You control it. Perpetual commercial/free license with full source code. No license keys or activation.
- High performance. Optimized algorithms with SIMD/multicore support. Optional links to vendor libraries.
- Trusted by leading companies. From physics research to finance.
ALGLIB is a full-stack numerical toolkit. Its features include:
ALGLIB is available in both Free and Commercial Editions.
To support scientific community we offer the same advanced set of algorithms
- from basic statistics and linear algebra to large-scale discrete optimization -
in both editions.
The Free Edition gives researchers, students and open-source projects full access to ALGLIB's functionality,
with licensing terms tailored to non-commercial use.
The Commercial Edition adds high-performance features (SMP/SIMD, native HPC kernels) and a business-friendly license.
ALGLIB Free Edition (
download):
+GPL or Personal/Academic license
+full set of numerical functionality
+extensive algorithmic optimizations
-single-threaded, no HPC kernels
-non-commercial license
ALGLIB Commercial Edition (
more information):
+flexible commercial license
+no royalties or distribution fees
+extensive algorithmic optimizations
+SMP, SIMD, commercial HPC kernels
+commercial support and warranties
Announcements
ALGLIB NEWS (archive):
01.02.2026 Last reminder: annual price review from February 15
29.12.2025 ALGLIB 4.07 is released, annual price review, plans for 2026
07.10.2025 ALGLIB 4.06.0, the first MINLP-capable version, is released!
09.06.2025 ALGLIB 4.05 is released, a glimpse of the upcoming MINLP solvers
Resources and links
ALGLIB User Guide online
Dense and sparse linear solvers
- dense direct linear solvers
- sparse iterative/direct linear solvers
Matrix operations and decompositions
- dense BLAS
- LU, Cholesky, QR/LQ and SVD decompositions
- matrix inversion, norms and condition numbers
- generation of random matrices
Sparse linear algebra
- Sparse BLAS
- LU, Cholesky decompositions
- linear solvers
- eigensolvers
Eigenvalues and eigenvectors
- dense symmetric/Hermitian EVD
- dense nonsymmetric EVD
- sparse symmetric EVD
Interpolation and fitting
- single-dimensional interpolation
- 1D, 2D and 3D splines
- fast scattered N-dimensional interpolation
- least squares curve fitting
Curve and surface fitting
- single-dimensional curve fitting
- 2D and N-D surfaces
- least squares curve fitting
Thin plate spline interpolation and fitting
- Thin plate splines
- Interpolation and fitting
- Large-scale algorithms
Inverse distance weighting
- IDW
- original, modified and modified-stabilized algorithms
Linear programming
- linear programming
- simplex method
- interior point method
Convex/non-convex QP and QCQP solver
- quadratic programming
- interior point method
Conic solver (SOCP and beyond)
- conic programming
- second-order cones
- power cones
Nonlinear programming
- nonlinear programming
- augmented Lagrangian methods
- SQP
- SLP
Optimization (nonlinear and quadratic)
- unconstrained nonlinear optimization
- constrained nonlinear optimization (box, linear, nonlinear constraints)
- constrained quadratic programming
- nonsmooth optimization
Multi-objective optimization solver
- Multi-objective optimization
Derivative-free optimization
Global optimization solver
- Global optimization solver
- Differential evolution
Mixed-integer nonlinear programming
- MINLP solvers
- Branch-and-bound
- DFO MINLP
FFT, convolution, correlation
- FFT
- convolution
- correlation
Data analysis: classification, regression, other tasks
- LDA, PCA
- hierarchical and k-means clustering
- decision forests
- nonlinear classifiers
Decision forest (regression and classification)
- Randomized trees and decision forests
- Regression and classification
- Variable importance
Time series analysis
- Filtering and smoothing
- Predicting
Statistics: general algorithms
Hypothesis testing
- parametric and non-parametric tests
Other algorithms
Special functions
Numerical integration
Nonlinear and polynomial equations
Differential equations
Other articles
DOCUMENTATION LICENSE:
1. ALGLIB User Guide is licensed for personal use only. See ALGLIB Reference Manual for a free documentation under BSD-like license
2. You may read the Guide and make unlimited copies for personal use.
3. Any other kinds of using the Guide, specifically, sales or any other commercial use,
distribution on any material media, through computer networks or any other ways, are prohibited.
