optim

Optimization library for Torch with various algorithms.

DecliningOpen SourceLow lock-in

Pricing

Free tier

Flat rate

Adoption

Cooling

License

Open Source

Data freshness

Aging · Jun 8, 2026

Overview

What is optim?

An optimization library for the Torch framework offering a variety of algorithms including SGD, Adagrad, Conjugate-Gradient, LBFGS, and RProp. It is essential for developers working on deep learning projects who require efficient optimization techniques.

Key differentiator

optim stands out by offering a comprehensive set of optimization algorithms directly integrated into the Torch framework, making it an essential tool for deep learning projects within this ecosystem.

Capability profile

Capability Radar

Ease of StartEcosystemValueMaturityFlexibilityScale Ready

Honest assessment

Strengths & Weaknesses

↑ Strengths

Variety of optimization algorithms including SGD, Adagrad, Conjugate-Gradient, LBFGS, and RProp.medium

Highly integrated with the Torch framework for seamless usage in deep learning projects.medium

Open-source nature allows for community contributions and improvements.medium

↓ Weaknesses

Limited Language Supporthigh

The library is primarily designed for Lua and has limited support for other languages, which can restrict its usability in diverse development environments.

Small Community and Limited Documentationmedium

Due to the niche nature of the tool and its primary focus on Lua, there is a smaller community contributing to it, leading to less comprehensive documentation and fewer resources for troubleshooting.

Performance Issues at Scalehigh

Optim may experience performance degradation when handling large datasets or complex models, which can be critical in deep learning applications where efficiency is paramount.

Complex Setup and Configurationmedium

Integrating Optim with existing Torch projects requires a detailed understanding of both the library's requirements and the project's architecture, leading to a more complex setup process.

Fit analysis

Who is it for?

✓ Best for

Teams working on Torch-based projects who need a robust set of optimization algorithms.

Researchers and developers looking for open-source solutions for deep learning model training.

✕ Not a fit for

Projects that require real-time optimization in production environments as it is self-hosted.

Developers preferring cloud-managed services over local installations.

Cost structure

Pricing

Free Tier

Available

Open source — free to use

Starts at

$0

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Next step

Get Started with optim

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →