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LLAMAEDGE

Run LLM inference apps locally or on the edge

Apache-2.0

ABOUT

Running LLMs locally is often tied to Python environments, GPU drivers, and heavy dependencies that conflict across projects and operating systems. LlamaEdge solves this by packaging LLM inference as cross-platform WebAssembly applications that run anywhere — Mac, Windows, Linux, or edge devices — with a single binary. No Python, no CUDA toolchain, no environment hell. Just download a GGUF model and a Wasm app, and run.

INSTALL
curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install_v2.sh | bash curl -LO https://github.com/LlamaEdge/LlamaEdge/releases/latest/download/llama-chat.wasm

INTEGRATION GUIDE

1. Run OpenAI-compatible LLM API servers locally without Python or complex GPU setup 2. Deploy LLM inference on edge devices and ARM-based infrastructure where Python runtimes are impractical 3. Serve multiple model types — text, embedding, speech, image — from a single portable runtime 4. Fine-tune and serve customized open-source LLMs locally for privacy-sensitive applications 5. Run batch inference on headless servers with zero runtime dependencies beyond WasmEdge

TAGS

llminferenceedgewasmlocalopen-sourcegguf
LlamaEdge — AI Tool | Agentic AI For Good