The Best distilabel Alternatives in 2026

Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.

A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.

Kale simplifies data science workflows for deploying Kubeflow Pipelines.

ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.

Kedro-Viz visualizes Kedro data and machine learning pipelines and tracks experiments.

ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.

Pachyderm provides data-focused pipelines and version control for datasets and related workflows.

Pathway offers cloud templates for RAG, AI pipelines, and enterprise search that stay synchronized with connected data sources.

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

Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.

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

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

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

ZenML provides a platform for machine learning pipelines and AI agents.

BentoML helps build and serve AI apps and models through inference APIs, job queues, and multi-model pipelines.

The Darknet neural network framework is written in C and CUDA and supports CPU and GPU computation.

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

DEAP provides a Python framework for prototyping evolutionary computation algorithms and testing new ideas.

The ChefBoost Python framework supports decision trees such as ID3, C4.5, CART, CHAID, regression trees, and ensemble methods.

DeepEval is an LLM evaluation framework, according to its repository description.

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

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

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

PyToune provides a simplified framework and utilities for working with PyTorch.