Floyd

Train, optimize, access libraries, and track ML models with real-time monitoring.

Free plan available
No credit card

What is Floyd?

Floyd is a platform designed to help machine learning practitioners train, optimise, and manage models without managing infrastructure themselves. It provides GPU access, model tracking, and real-time monitoring capabilities in one place. The platform is aimed at data scientists, ML engineers, and teams who want to focus on model development rather than server setup and maintenance. Floyd handles the computational resources and logging, allowing you to experiment faster and keep organised records of your work.

Key features

GPU access

Run training jobs on remote GPUs without setting up your own hardware

Model tracking

Log experiments, parameters, and results to compare model versions

Real-time monitoring

Watch training progress and resource usage as jobs run

Library access

Pre-installed ML frameworks and libraries ready to use

Job management

Queue, schedule, and organise multiple training runs

Integration

Connect with version control and notebook environments

Pros & cons

Advantages

Removes infrastructure setup overhead; start training immediately
Built-in experiment tracking makes it easy to compare model performance across runs
Pay only for compute used on the free tier, scaling up as needed
Real-time monitoring helps you catch issues early in training

Limitations

Limited to the platforms and frameworks Floyd supports; less flexibility than self-hosted solutions
Costs can accumulate quickly with large-scale or long-running experiments
Smaller community and fewer integrations compared to larger ML platforms