The Best Cog Alternatives in 2026

ORMB packages machine learning models as OCI artifacts, in a workflow described as Docker for ML models.

ModelDB tracks machine learning model versions, metadata, and experiments.

Flexible, high-performance serving system for machine learning models.

Train and run models with OneFlow, a scalable deep learning framework for distributed machine learning workloads.

The Hydrosphere repository describes an MLOps platform for machine learning operations.

DJL is a Java framework for running deep learning models across different engines.

dstack coordinates AI compute and supports training and inference across GPU clouds, Kubernetes, VMs, and bare metal.

Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.

Apache SINGA supports distributed deep learning through a system and library for model training.

DeepDetect provides a deep learning server and command-line interface for Torch and TensorRT.

Sagify describes its project as a way to work with large language models and machine learning more easily.

Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.

ONNX-MLIR compiles ONNX models using MLIR compiler infrastructure for model deployment workflows.

Model deployment for AI applications is supported by nndeploy, a framework described as easy to use and high performance.

MMDeploy provides a model deployment framework from the OpenMMLab project.

PAI schedules resources and manages clusters for AI workloads across distributed computing environments.

Machine learning operations and large language model operations are the focus of Starwhale’s platform.

Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.

TPOT uses genetic programming to optimize machine learning pipelines in Python.

The Datumbox framework is written in Java for developing machine learning and statistical applications.

Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.

The linfa project provides a machine learning framework written in Rust.

Hypernets offers a general automated machine learning framework for developing end to end AutoML toolkits in specific domains.

MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.