What it does

This is a curated markdown table of cloud GPU providers, deployment platforms, and MLOps tools—roughly 70 entries across three categories. Each row lists pricing, free trial availability, and referral perks. Think of it as a comparison-shopping cheat sheet for anyone whose laptop fan sounds like a jet engine during model.fit().

The interesting bit

The value isn’t the code—there isn’t any. It’s the legwork: hunting down $10 Paperspace credits, fast.ai forum coupon codes, Google’s 1000-TPU research cluster, and the fact that most “cheap” GPU providers are just reselling AWS/GCP anyway. The README is refreshingly honest about this in the footnotes.

Key highlights

• Free tier map: Colab and Kaggle Kernels are “FREE FOREVER*"—asterisk meaning limited session time
• Credit scavenging: GitHub Student Pack ($110 AWS), Google Startup Program ($1K–$100K), Nvidia academic grants
• MLOps included: Separate table for platforms like Flyte, Kubeflow, MLflow, plus commercial options
• Deployment appendix: Heroku (model <500MB), Streamlit Cloud, Vercel, etc.
• Peer-to-peer oddity: Golem, a decentralized compute marketplace, makes a cameo

Caveats

• Pricing data is static and self-reported; the author notes you should “recheck with the provider”
• Some entries are just names with dashes for pricing—clearly incomplete
• No filtering, search, or API; Ctrl-F is your interface

Verdict

Grab this if you’re a student, bootstrapped founder, or hobbyist trying to avoid cloud bill shock. Skip it if you need programmatic infrastructure management or real-time pricing—this is a reference, not a tool.