gym
A toolkit for developing and comparing reinforcement learning algorithms.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is gym?
Gym is a toolkit for developing and comparing reinforcement learning algorithms. It provides a standard API to interact with environments, making it easier to test different RL methods across various tasks.
Key differentiator
“Gym provides a standardized and extensible framework for developing, testing, and comparing reinforcement learning algorithms across various environments.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Custom environment integration requires significant effort and documentation is sparse on this topic
Gym's architecture can lead to performance issues when scaling up the number of parallel environments
Fit analysis
Who is it for?
✓ Best for
Researchers looking to benchmark their reinforcement learning algorithms against standard environments
Developers who need a consistent API for interacting with various reinforcement learning environments
✕ Not a fit for
Projects requiring real-time interaction with physical systems (due to its local nature)
Teams needing cloud-based solutions for large-scale RL training
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
Alternatives
Works well with
Integrations
Next step
Get Started with gym
Step-by-step setup guide with code examples and common gotchas.