Determined
Scalable deep learning training platform with distributed support and experiment tracking.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Determined?
Determined is a scalable deep learning training platform that supports distributed training, hyperparameter tuning, experiment tracking, and model management. It helps data scientists and engineers efficiently develop and deploy machine learning models at scale.
Key differentiator
“Determined stands out by offering a comprehensive, open-source solution for scalable deep learning training that includes distributed computing and robust experiment management features.”
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
Primary SDK is Python-based with limited official support for other languages
Requires detailed YAML configurations for experiment tracking and distributed training setups
Fit analysis
Who is it for?
✓ Best for
Teams needing scalable distributed training capabilities for deep learning projects
Organizations that require robust hyperparameter tuning and experiment tracking features
Developers who need to manage multiple versions of machine learning models
✕ Not a fit for
Projects with limited computational resources as it requires significant infrastructure setup
Teams preferring cloud-based managed services over self-hosted solutions
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
Works well with
Next step
Get Started with Determined
Step-by-step setup guide with code examples and common gotchas.