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argmin-rs/argmin

Numerical optimization in pure Rust observed · 2026-08-28

github.com/argmin-rs/argmin · homepage · Rust · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

60/100

  • Activity 51
  • Release rhythm 50
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 0
  • age_days: 2964
  • days_rel: 335
  • days_push: 299
  • n_releases_24m: 6

Full methodology

Adoption not part of the score

1275 stars · 116 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

argmin is a numerical optimization library written entirely in pure Rust, offering a wide range of optimization algorithms behind a consistent, type-agnostic interface. It supports pluggable math backends like ndarray and nalgebra, observers for tracking iteration progress, and optional checkpointing for resilience.

Use cases

  • minimize a cost function in Rust
  • run gradient descent or Newton-type solvers
  • fit a model by numerical optimization
  • implement a custom optimization solver with a consistent framework
  • swap between ndarray and nalgebra math backends
  • resume long optimization runs after crashes via checkpointing

When to choose

  • you need optimization algorithms in pure Rust without C/Fortran dependencies
  • you want a consistent interface to try multiple solvers on the same problem
  • you need type-agnostic math with your own types or backend
  • you want observers and checkpointing for long-running optimizations

When to avoid

  • you need a batteries-included scientific computing stack like SciPy
  • you work primarily in Python or another language
  • you need symbolic or mixed-integer optimization rather than numerical continuous optimization

Facets

library · maturity active

math machine-learning mathematics data-science performance rust cross-platform numerical-optimization optimization-algorithms solvers gradient-descent type-agnostic checkpointing algorithms

3 sources

Member repositories

RepositoryRoleHealth v2
argmin-rs/argminmain60

For agents

markdown · JSON · MCP: product_card(name="argmin-rs/argmin")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem