gonum/gonum

Health v2 · maintenance only

Adoption not part of the score

8427 stars · 581 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Gonum is a suite of numerical and scientific computing libraries for Go, covering matrices and linear algebra, statistics and probability, optimization, differentiation, integration, and graph/network analysis. It is written in pure Go with optional assembly for performance and follows a regular release schedule aligned with Go releases.

Use cases

• perform matrix and linear algebra operations in Go
• compute statistics and sample from probability distributions
• optimize or integrate numerical functions
• build and analyze graphs and networks
• do scientific computing and data analysis in Go without C dependencies

When to choose

• you need performant numerical code in Go with transparent, pure-Go sources
• you want composable, well-tested scientific libraries with a regular release cadence
• you need graph algorithms or statistics alongside linear algebra in one ecosystem

When to avoid

• you need GPU-accelerated deep learning or tensor frameworks like PyTorch
• you require the breadth of SciPy/NumPy ecosystems or their tooling
• you need guaranteed identical floating-point results across architectures

Facets

library · maturity active

math data-science machine-learning graphics data-science mathematics developer-tools go windows cross-platform linear-algebra statistics optimization graph-analysis scientific-computing matrices numerical-methods algorithms linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="gonum/gonum")