The Best Nebullvm Alternatives in 2026

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

FastChat offers an open platform for training, serving, and evaluating large language models, and hosts release repositories for Vicuna and Chatbot Arena.

DeepLake provides multimodal data infrastructure for AI agents, including retrieval and training.

traceAI provides open source tracing for AI applications and frameworks using OpenTelemetry.

Helicone provides open-source observability for LLM applications, with tools to monitor, evaluate, and experiment.

Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.

TensorRT-LLM provides Python and C++ runtimes with optimizations for language model inference on NVIDIA GPUs.

Forefront provides a platform for fine tuning and running inference with open source language models.

Upstage builds large language models and document-processing engines for workplace workflows.

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

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

GPT-NeoX implements model parallel autoregressive transformers on GPUs using Megatron and DeepSpeed libraries.

This repository describes technologies for enabling AI capabilities with large and multimodal language models.

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

DeepEval is an LLM evaluation framework.

Lucent brings the Lucid library approach to PyTorch, according to its repository description.

The Feast repository describes an open source feature store for AI and machine learning projects.

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

The tensorflow-upstream repository provides a ROCm port of TensorFlow for the project.

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

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

Xinference runs language, speech, and multimodal models through a unified inference API across cloud, on premises, or laptop setups.

Mirascope describes itself as an alternative approach to building applications with large language models.

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