RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.
Liquid AI — Device-native foundation models.
Liquid AI is an efficiency-first foundation model company. We build highly capable, compute-optimized models that bring intelligence to any device and medium of choice.
Coasts — Containerized Hosts for AI Agents
Free, open source parallel runtimes for AI agents. Run multiple isolated environments on your machine — no cloud, no conflicts.
Build Bigger With Small Ai: Running Small Models Locally
Together AI | The AI Native Cloud
Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.
Introducing LM Studio Bionic: the AI agent for open models
The AI agent made for open models, built to get things done.
Cloudflare Workers AI | Open-source AI inference
Workers AI facilitates the scalable development & deployment of AI applications at the edge.
Apptainer - Portable, Reproducible Containers
Apptainer is an open source container platform designed to run complex applications on high-performance computing (HPC) clusters in a simple, portable, and reproducible way.
Understanding Spec-Driven-Development: Kiro, spec-kit, and Tessl
Notes from my Thoughtworks colleagues on AI-assisted software delivery
Mirai Labs: Frontier On-Device AI Lab
Models, runtime & infrastructure to make on-device AI interactive, ambient & continuous.
Wafer - Ship the fastest inference in the world
Autonomous AI agents that profile, diagnose, and optimize GPU inference across your entire stack — from kernels to models to production pipelines.
GradientHQ/parallax
Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere
Automotive — Solutions — Liquid AI
On-device AI for automakers — real-time, personalized in-car assistants that run on the vehicle's existing CPUs and NPUs.
google-ai-edge/gallery
A gallery that showcases on-device ML/GenAI use cases and allows people to try and use models locally.
Models.dev — An open-source database of AI models
Models.dev is a comprehensive open-source database of AI model specifications, pricing, and features.
Getting Started with ML and AI in Research Software | Software Sustainability Institute
Getting started with ML in research software means embracing a shift in how results are produced and reproduced. Instead of a fixed execution path, research software teams work with systems whose behaviour emerges from data, configuration, and training dynamics. Reproducibility becomes a matter of capturing the process rather than relying solely on the code. The tools and techniques outlined here can be adopted incrementally into existing projects, and together they provide a practical foundation for reproducible ML research.
Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face
Generative artificial intelligence (AI) and machine learning (ML) models are being adopted across a variety of domains. As these technologies develop, there is notable diversity in their levels of availability and paths of diffusion. For example, fully closed-source models may be available through chatbots and API calls, but their weights, source code, training data, and other artifacts remain hidden from view. In contrast, open models make some or all of these materials publicly available for developers and downstream users.