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BentoML

Unified model serving framework for building production AI applications and LLM backends.

LicenseApache-2.0
GitHub stars7.5k
Last commit1 weeks ago
Tags6 topics
Mlops PlatformDynamic BatchingLlm DeploymentModel ServingDeveloper ToolsPython
Overview

Why consider BentoML?

BentoML is an open-source AI and LLM serving framework written in Python. It packages PyTorch, TensorFlow, Transformers, and custom ML pipelines into high-throughput containerized services with adaptive dynamic batching, multi-GPU orchestration, and OpenAPI endpoints.

Guided learning

Learn BentoML by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 2 sections
In this guide2 sections

Overview of BentoML

BentoML builds scalable REST and gRPC model serving runtimes with hardware-accelerated batching.

Quickstart

bash
1pip install bentoml
2bentoml serve service:svc

BentoML is licensed under the Apache License Version 2.0.

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BentoML FAQs

BentoML is listed as a Developer Tools tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository and official website for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

BentoML is listed under the Apache-2.0 license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

BentoML is listed as an alternative to TorchServe. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.