The Best qkeras Alternatives in 2026

PaddlePaddle provides a deep learning framework for training models across devices and platforms.

The MegEngine framework supports deep learning and automatic differentiation, according to its repository description.

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

FATE supports federated learning through an industrial grade framework.

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

The fuku-ml project provides a machine learning library described as simple to use.

MLX provides an array computing framework designed for Apple silicon devices.

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

Sinabs supports fast training of spiking neural networks with PyTorch and inference on neuromorphic hardware.

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

PyTorch Ignite provides a high level library for flexibly training and evaluating neural networks.

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

Cascade supports MLOps workflows for smaller projects without a full platform.

List of awesome compiler projects and papers for tensor computation and deep learning.

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

Maze provides an applied reinforcement learning framework for developing projects in Python.

ModelFox supports training, deployment, and monitoring for machine learning models.

This repository contains machine learning code examples that use Comet.ml.

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

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

Burn provides a flexible, efficient, and portable tensor library for building deep learning applications.

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

TensorFlow offers an open-source machine learning platform with tools, libraries, and community resources.

Adaptive Reliability Layer decides when to retrain a model based on drift signals and delayed labels.