BentoML

Overview

BentoML is an open-source Python framework for packaging and deploying machine learning models as production-ready APIs. It handles model serving, inference pipelines, and job queues, allowing developers to turn trained models into scalable endpoints.

Best for

Best for
Python developers who need to quickly deploy ML models as scalable APIs

Use cases

• Deploying a trained model as a REST API endpoint
• Building multi-model inference pipelines for complex workflows
• Serving LLM applications with job queue management

Notes

BentoML is an open-source Python framework for packaging and deploying machine learning models as production-ready APIs. It handles model serving, inference pipelines, and job queues, allowing developers to turn trained models into scalable endpoints.

8,663 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

• Deploying a trained model as a REST API endpoint
• Building multi-model inference pipelines for complex workflows
• Serving LLM applications with job queue management

Pros

• Simplifies model serving with built-in API and pipeline abstractions
• Strong community support with over 8,600 GitHub stars
• Python-native, easy to integrate with existing ML workflows

Cons

• Limited to Python ecosystem, not suitable for non-Python stacks
• May require additional infrastructure for high-scale production deployments
• Documentation can be sparse for advanced use cases

Indexed from awesome-llmops and enriched against its public facts.