LM Studio

Run LLMs locally with one command

Tool for running large language models locally on your machine with a simple CLI interface. Download and run Llama 3, Mistral, Gemma, Phi, Code Llama, and dozens of other open-source models with a single command. Features model management, GPU acceleration (NVIDIA/AMD/Apple Silicon), OpenAI-compatible API server, Modelfile for customization, and multi-model switching. Ideal for offline AI development, privacy-sensitive use cases, and local testing. 120K+ GitHub stars.

Self-hosted AI platform with ChatGPT-like interface for local and cloud LLMs.

Extensible, self-hosted AI platform with 290M+ Docker pulls and 124K+ GitHub stars. Supports Ollama, OpenAI-compatible APIs, and any Chat Completions backend. Features built-in RAG, multi-user RBAC, voice/video calls, Python function workspace, model builder, and web browsing. Runs entirely offline with enterprise features including SSO and audit logging.

Find which AI models actually run on your hardware in one command

llmfit is a Rust-based terminal tool that matches over 200 LLM models from 30+ providers against your exact hardware specs. The interactive TUI scores each model on fit, speed, VRAM usage, and context length, helping you avoid downloading models that won't run on your machine. It supports Ollama, llama.cpp, MLX, Docker Model Runner, and LM Studio backends.

Run open-source LLMs on your phone, fully offline and private

Google AI Edge Gallery is an open-source mobile app that lets you download and run large language models like Gemma directly on Android and iOS devices with zero cloud dependency. Built on MediaPipe and LiteRT, it features AI chat with reasoning mode, multimodal image analysis, real-time audio transcription, and autonomous agent skills—all running entirely on-device for complete privacy. A reference implementation for developers building offline-first AI experiences.

Container-native local AI model serving with Podman

RamaLama is an open-source tool that containerizes AI model inference using Podman or Docker, eliminating host system configuration complexity. It auto-detects GPUs (NVIDIA, AMD, Intel, Apple Silicon), pulls models from HuggingFace, Ollama, and OCI registries, and runs them in isolated rootless containers with read-only mounts and network isolation. Developed under the Containers project (Red Hat ecosystem), it brings familiar container workflows to local LLM serving.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Hugging Face's open-source inference server for embeddings, rerankers, and classifiers

Text Embeddings Inference is Hugging Face's Apache-2.0 server for high-throughput embedding, reranking, and sequence-classification models. TEI packages token-based dynamic batching, optimized Transformers kernels, Safetensors loading, OpenAI-compatible embedding endpoints, Prometheus metrics, and configurable OpenTelemetry tracing in deployable CPU and GPU images.

Open-source toolkit for quantizing, deploying, and serving LLMs and vision-language models

LMDeploy is an Apache-2.0 toolkit for self-hosting LLM and vision-language model inference with TurboMind and PyTorch engines. It combines continuous batching, blocked KV cache, tensor parallelism, AWQ and KV-cache quantization with OpenAI-compatible APIs, multi-GPU distribution, offline pipelines, and production metrics.

Multi-agent model API that orchestrates frontier models behind one OpenAI-compatible endpoint

Sakana Fugu is a hosted model-provider API that exposes a learned multi-agent system as one OpenAI-compatible model. It dynamically routes coding, code review, research, and reasoning tasks across a frontier-model pool, with Fugu for lower-latency work and Fugu Ultra for harder workloads where answer quality matters more than cost or speed.

Lifelike AI voice generation, cloning, and voice agents

ElevenLabs is an AI voice platform for text-to-speech, voice cloning, and conversational AI agents, built on models like Multilingual v2 and the low-latency Flash v2.5 and Turbo v2.5. Developers call its API to generate lifelike narration, clone voices from short audio samples, dub content across 30+ languages, add sound effects, and deploy real-time voice agents for customer service, IVR, and interactive apps, with SDKs for Python, JavaScript, and more.

Official Python SDK for the xAI API

The xAI Python SDK is the official Python client for the xAI API, giving developers a direct way to build Grok-powered apps without relying on community proxies or unofficial wrappers. It supports synchronous and asynchronous Python clients for chat completions, streaming responses, function/tool calling, and multimodal workflows, making it a clean fit for backend services, agents, notebooks, and developer tools that need programmatic xAI access.