Open Source
BentoML
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Our verdict
We have not reviewed BentoML yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About BentoML
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
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
8,663 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
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
Key facts
What we have checked
- Latest version
- 1.4.40 (released 23 Oct 2026)
- GitHub stars
- 8,865
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How BentoML is growing
8,663 to 8,865
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 1.4.40
Released 1.4.39
Released 1.4.38
Released 1.4.37
Released 1.4.36
Released 1.4.35
Released 1.4.34
Released 1.4.33
Released 1.4.32
Released 1.4.31
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Keras
Community
Deep Learning for humans
PyTorch
Community
Tensors and Dynamic neural networks in Python with strong GPU acceleration
scikit-learn
Community
scikit-learn: machine learning in Python
TensorFlow
Community
An Open Source Machine Learning Framework for Everyone
vLLM
Community
A high-throughput and memory-efficient inference and serving engine for LLMs
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.