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Ray Serve

Inference & Serving 8.3/10 Strong

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Ray Serve scores 8.3/10 (Strong) in Inference & Serving.

Language Python License Apache-2.0 Stars 43.1k★ Type library Self-host Yes Repo ray-project/ray Homepage https://docs.ray.io/en/latest/serve/index.html

Quality

Strong 8.3
Adoption 66
Activity 97
Maturity 100
Community 73
Capability 50
Show the math
Overall 8.3/10
value = 8.3/10
score = value
Adoption 6.9/10
value = 65.9/100
score = 1 + 9 * value / 100
Activity 9.7/10
value = 96.8/100
score = 1 + 9 * value / 100
Maturity 10/10
value = 100/100
score = 1 + 9 * value / 100
Community 7.6/10
value = 72.9/100
score = 1 + 9 * value / 100
Capability 5.5/10
value = 50/100
score = 1 + 9 * value / 100

Key metrics

43.1k★ GitHub stars
1.1k/90d Recent commits
47 devs/90d Recent contributors
9.7y Project age
active Last commit

Gotchas

No gotchas documented yet. Contribute one if you know a constraint we missed.

Labels

  • Self-hosted

    Self-hosted

    You deploy and operate it yourself; there is no hosted option here.

distributed scaling pipelines python serving