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Project comparison
BentoML vs Ray
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
BentoML
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
8.6K
Stars
+13
Weekly
58/100
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
Ray has the larger GitHub footprint with 42.5K 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 | BentoML | Ray |
|---|---|---|
| GitHub stars | 8.6K | 42.5K |
| Weekly growth | +13 | +72 |
| Health score | 58 | 79 |
| Contributors | 236 | 1.6K |
| Commits per week | 2.5 | 87.6 |
| Open issues | 142 | 3.5K |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last commit | 5d ago | 15h ago |
| Last release | v1.4.39 | ray-2.55.1 |
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