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MLC-LLM
Universal LLM deployment with ML compilation
Apache-2.0
ABOUT
Deploying LLMs across diverse hardware (GPU, CPU, mobile, web) traditionally requires separate optimization stacks and manual tuning for each target platform. Developers must rewrite inference code for each backend, making cross-platform LLM deployment costly and error-prone. MLC-LLM solves this by using machine learning compilation to automatically optimize and deploy models from a single codebase to any target, achieving native performance on CUDA GPUs, Metal on Apple Silicon, Vulkan on Android, and WebGPU in browsers — all without per-platform rewrites.
INSTALL
pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightlyINTEGRATION GUIDE
1. Deploy LLMs natively on macOS, iOS, Android, and web browsers with GPU acceleration
2. Run large language models locally on consumer hardware without cloud dependencies
3. Build cross-platform AI applications that share a single model deployment pipeline
4. Optimize LLM inference for edge devices where traditional serving stacks cannot run
TAGS
pythoninferencedeploymentcompilationgpucpumobile