A vLLM-style inference server for Apple Silicon with a native MLX backend, exposing both OpenAI and Anthropic compatible APIs in a single process, featuring multimodal unified serving, continuous batching, paged KV cache, and SSD-tiered caching.
A local proxy that automatically routes each LLM request to the cheapest still-capable model
The first experimental fully peer-to-peer distributed AGI system where intelligence compounds continuously through autonomous agent networks, supporting decentralized training across heterogeneous devices, P2P inference routing, and a built-in blockchain micropayment economy.
A local AI inference engine for Apple Silicon with OpenAI-compatible API, supporting multi-modal, tool calling, and smart cloud routing.
A local-first personal AI agent framework from Stanford that enables offline agent orchestration, skill import, and trace-driven continuous learning through five composable primitives, supporting 10+ inference backends and four interaction modes.
A Docker Compose-based CLI orchestrator for local LLM stacks — spin up pre-wired inference backends, frontend UIs, RAG, voice, image generation, and more with a single command
A KVCache-centric disaggregated architecture platform for LLM serving, providing distributed KVCache pooling, topology-aware high-speed transfer engine, and centralized scheduler, supporting Prefill-Decode separation and MoE elastic inference.
LLM inference in C/C++ achieving state-of-the-art performance on local or cloud with minimal setup via the GGUF format and multi-hardware backend support.
A high-performance OpenAI-compatible API server for MLX models on Apple Silicon, supporting text, vision, audio transcription, and image generation/editing.
A distributed inference framework for running frontier LLMs across local device clusters, built on Apple MLX and libp2p, featuring automatic device discovery, topology-aware parallelism, and multi-API compatibility.
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