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Project comparison
Made With ML vs Ray
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Made With ML
Learn how to develop, deploy and iterate on production-grade ML applications.
47.6K
Stars
0
Weekly
36/100
Health
Ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
42.5K
Stars
+72
Weekly
79/100
Health
Quick Take
Adoption
Made With ML has the larger GitHub footprint with 47.6K stars.
Momentum
Ray is currently growing faster at +72 stars this week.
Maintenance
Ray has the stronger health score at 79/100.
Side-by-side Metrics
| Signal | Made With ML | Ray |
|---|---|---|
| GitHub stars | 47.6K | 42.5K |
| Weekly growth | 0 | +72 |
| Health score | 36 | 79 |
| Contributors | 1 | 1.6K |
| Commits per week | 0.1 | 87.6 |
| Open issues | 25 | 3.5K |
| Language | Jupyter Notebook | Python |
| License | MIT | Apache-2.0 |
| Last commit | 2mo ago | 15h ago |
| Last release | v1.1.0 | ray-2.55.1 |
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