12 Machine Learning Model Serving Tools (2026)

12 machine learning model serving tools — every link checked and refreshed for 2026.

BentoML

BentoML (now Bento) is an inference platform for deploying and scaling AI models, simplifying ML model deployment at production scale.

Cortex (acquired by Databricks)

Cortex, the realtime model serving project, joined Databricks in 2022; its serving capabilities now live on in Databricks Model Serving for deploying ML and GenAI models at scale.

TensorFlow Serving

TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments.

TorchServe is a flexible and easy to use tool for serving PyTorch models. Note: the project is now in Limited Maintenance mode – existing releases remain available but no new features or fixes are planned.

KServe

KServe enables serverless inferencing on Kubernetes and provides performant, high abstraction interfaces for common ML frameworks like TensorFlow, XGBoost, scikit-learn, PyTorch, and ONNX to solve production model serving use cases.

Multi Model Server (MMS)

Multi Model Server (MMS) is a tool for serving deep learning models exported from MXNet or the Open Neural Network Exchange (ONNX).

NVIDIA Dynamo-Triton (formerly Triton Inference Server)

NVIDIA Dynamo-Triton, formerly Triton Inference Server, deploys trained AI models from any framework (TensorFlow, TensorRT, PyTorch, ONNX Runtime) from local storage or cloud on GPU- or CPU-based infrastructure.

ForestFlow

ForestFlow is a scalable policy-based cloud-native machine learning model server for easily deploying and managing ML models.

DeepDetect

DeepDetect is an open-source deep learning API and server along with a pure web platform for training and managing models.

Seldon

Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimise risk through interpretable results and transparent model performance.

MLflow Models

An MLflow Model is a standard format for packaging ML models that can be used in a variety of downstream tools – for example, real-time serving through a REST API or batch inference on Apache Spark.

OpenVINO Model Server

OpenVINO Model Server (OVMS) is a high-performance system for serving machine learning models, optimized for Intel architectures.