The Best Kubeflow Alternatives in 2026

Build machine learning applications with Delta, an open-source framework implemented in Rust.

Catniff provides JavaScript developers with a Torch-like deep learning framework.

The cONNXr project provides a pure C runtime for ONNX models intended for embedded devices.

MLOps framework to package, deploy, monitor and manage thousands of production machine learning models.

Cortex provides cloud infrastructure for deploying, managing, and scaling machine learning models in production.

Infer.NET runs Bayesian inference in graphical models for a range of machine learning problems.

Espresso AI uses machine learning to optimize Snowflake and Databricks data warehouses and reduce query and infrastructure costs.

Caffe provides an open framework for building and running deep learning models.

Deep learning in Rust, with shape checked tensors and neural networks.

Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.

Tensors and Dynamic neural networks in Python with strong GPU acceleration.

Kale simplifies data science workflows for deploying Kubeflow Pipelines.

Extensible Toolkit for Finetuning and Inference of Large Foundation Models.

Nos dynamically partitions GPU resources and manages quotas in Kubernetes clusters.

OpenModelZ scales LLM inference on Kubernetes with engines including vLLM, SGLang, and LMDeploy.

Kubeflow makes deployment of ML Workflows on Kubernetes straightforward and automated.

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

Candle provides a minimalist Rust framework for machine learning model development and execution tasks.

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

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

Stakpak runs an agent on a machine to ship code and keep applications running.

Gymnasium provides a standard API for single agent reinforcement learning environments and related utilities.

Curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning.

DyNet provides tools for building dynamic neural networks and deep learning models.