LLM InfrastructureOpen Source✦ Free Tier
Ray
Distributed computing framework for ML workloads
⭐ 33,000 stars● Health 75 — ActiveDev Productivity & App Infrastructure
About
Open-source distributed computing framework for scaling Python ML workloads. Ray Serve and Ray Train power production LLM serving and fine-tuning pipelines.
Choose Ray when…
- •You need distributed computing for ML workloads
- •You're scaling training or inference across many machines
- •Python-native distributed batch processing is required
Builder Slot
Where do your models actually run?Required for most stacks
LLM providers and inference servers — where the actual model computation happens
Dev Tools
Not applicable
App Infra
Required
Hybrid
Required
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