Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.
Open source
24 alternativesBentoML
BentoML helps build and serve AI apps and models through inference APIs, job queues, and multi-model pipelines.
About BentoML
BentoML is an open-source Python library for building online serving systems for AI apps and model inference. It turns a model inference script into a REST API server using standard Python type hints, and it supports serving multi-model systems built from open-source or custom models.
BentoML packages code, models, and dependency configuration into a deployable artifact called a Bento, and it can generate Docker images from that artifact. Its listed serving features include dynamic batching, model parallelism, multi-stage pipelines, and multi-model inference-graph orchestration. Services can be developed and run locally before being deployed with Docker containers or BentoCloud. BentoCloud is a separate cloud service, and the source does not describe its terms or pricing. The source states that the library requires Python 3.9 or later, and that Docker must be running to generate container images.
Key features
- Turns model inference scripts into REST API servers using Python type hints
- Packages code, models, and dependencies into a deployable artifact called a Bento
- Generates Docker images from a configuration file for deployment
- Built-in serving optimizations including dynamic batching and model parallelism
- Multi-stage pipeline and multi-model inference-graph orchestration
- Local development with a command that starts the service on localhost
Best for: Python developers and machine learning teams who need to serve AI models or multi-model pipelines as inference APIs.
Good for
- Open-source project with a public GitHub repository
- Source states it supports any ML framework, modality, and inference runtime
- Docker image generation is intended to reduce dependency management when deploying
Watch out for
- Requires Python 3.9 or later
- Container image generation requires Docker to be running
BentoML at a glance
- Website
- github.com/bentoml/BentoML
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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BentoML FAQ
Which Python version is required?
The installation instructions state that BentoML requires Python 3.9 or later.
How do I run a BentoML service locally?
Install the model's dependencies, such as PyTorch and Transformers, then run bentoml serve. The service runs at http://localhost:3000 by default.
How is a service prepared for Docker deployment?
Run bentoml build to package the code, models, and dependencies into a Bento, then run bentoml containerize to generate a Docker image.
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