BentoML · Rate Limits

Bentoml Rate Limits

BentoCloud does not publish fixed platform-level API rate limits. Instead, concurrency and throughput are governed by per-deployment configuration. Each BentoML service deployment defines its own concurrency ceiling and scaling bounds. BentoCloud autoscales replicas to meet demand within the configured min/max replica range. An optional external request queue can buffer excess traffic to prevent overload. Specific platform quotas (API management calls, organization-level limits) are not publicly documented and may vary by plan tier; contact BentoML sales for enterprise quota details.

Bentoml Rate Limits is the machine-readable rate-limit profile for BentoML on the APIs.io network, conforming to the API Commons Rate Limits specification.

It captures 6 rate-limit definitions.

Tagged areas include machine learning, model serving, inference, AI, and REST API.

6 Limits
machine learningmodel servinginferenceAIREST APIMLOpsdeploymentGPULLMBentoCloud

Limits

Service Concurrency per-replica
Minimum Replicas per-deployment
Maximum Replicas per-deployment
Request Timeout per-service
External Queue Buffering per-deployment
Autoscaler Stabilization Window per-deployment