ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.
Open source
24 alternativesMosec
Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.
About Mosec
Mosec is an open-source framework for serving trained machine learning models as online APIs and microservices. Developers define a service in Python by subclassing Worker and implementing a forward method, reusing offline model code.
It aggregates requests from different users for batched inference and runs pipelined stages in separate processes for mixed CPU, GPU and IO work. It provides model warmup, graceful shutdown and Prometheus metrics for use with container orchestration. Installation requires Python 3.7 or above on Linux or macOS.
Key features
- Aggregates requests from different users for batched inference
- Runs pipelined stages in separate processes for mixed workloads
- Defines model services in Python by subclassing Worker
- Handles model warmup, graceful shutdown and Prometheus metrics
- Supports Msgpack serialization for binary payloads such as images
- Runs under Kubernetes or other container orchestration systems
Best for: Best for Python developers serving trained models as APIs with batching and staged CPU/GPU processing.
Good for
- Python interface works across ML frameworks using offline testing code
- Web layer and task coordination use Rust with async I/O
- Includes warmup, graceful shutdown and Prometheus metrics for cloud deployment
Watch out for
- Package install commands are documented for Linux or macOS only
- Building from source requires installing Rust
- Requires Python 3.7 or above
Mosec at a glance
- Website
- github.com/mosecorg/mosec
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Mosec FAQ
How do I install Mosec?
It requires Python 3.7 or above. On Linux or macOS install with pip install -U mosec, conda install conda-forge::mosec, or pixi add mosec. To build from source, install Rust and run make package.
How do I define a model service?
Create a class that inherits mosec.Worker, load the model in __init__, and override the forward method to process single or batched inputs and return results.
How is Mosec run in production?
It is designed to run in the cloud with model warmup, graceful shutdown and Prometheus metrics, managed by Kubernetes or other container orchestration systems.
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