#16 · Primary category: Inference & Local Deploy
mlc-llm
Universal LLM Deployment Engine with ML Compilation
Project last updated:08/17/26
GitHub Stars
23.1K
Forks
2.1K
Contributors
164
License
Apache-2.0
Why we included this project
MLC LLM is a compiler-based inference engine that turns large language models into optimized native code for the hardware you actually have, from NVIDIA and AMD GPUs to Apple silicon, Intel GPUs, phones, and browsers. That makes it a strong pick for teams that want to run models on-premises or on edge devices rather than renting cloud GPUs, since the same model can be compiled once and deployed across very different targets. It also exposes an OpenAI-compatible API through a REST server, with bindings for Python, JavaScript, iOS, and Android, so it drops into existing tooling without much friction. If you care about getting good performance out of consumer or mobile hardware, or keeping inference fully self-hosted, this is worth a close look.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
ollama
Get up and running with Kimi-K2.6, GLM-5.2, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
llama.cpp
LLM inference in C/C++
vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
LocalAI
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.