MLC LLM
A compiler and inference engine for running large language models natively across GPUs, phones and browsers.
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About MLC LLM
MLC LLM is a machine learning compiler and deployment engine for large language models. Its MLCEngine runs models on AMD, NVIDIA, Apple and Intel GPUs through Vulkan, CUDA, ROCm and Metal, in web browsers through WebGPU, and on iOS and Android devices.
The same engine is exposed as an OpenAI-compatible REST server and through Python, JavaScript, iOS and Android APIs. It suits developers who want to compile and serve models on their own hardware rather than end users looking for a chat app.
Strengths
- Broad hardware support across Vulkan, CUDA, ROCm, Metal and WebGPU
- OpenAI-compatible REST server
- One engine for desktop, mobile and browser deployments
Limitations
- Aimed at developers rather than casual users
- Model compilation adds setup steps
Details
- Pricing
- FreeFree and open source under the Apache 2.0 licence.
- License
- Apache-2.0
- Developer
- The MLC AI contributors
- Platforms
- Windows, macOS, Linux, Command line
- How it runs
- Downloadable app
- Account
- Not required
- Works offline
- Yes
- Best suited for
- Developers deploying language models on local GPUs, mobile devices or in the browser
- Categories
- Local AI tools, AI developer tools
- Last verified
- Added
Alternatives to MLC LLM
Compare allSoftware that can replace MLC LLM for an important use case, and what changes if you switch.
llama.cpp
The C++ engine most local AI apps are built on, running language models on ordinary hardware.
llama.cpp runs models as a single dependency-free binary with CUDA, Vulkan, HIP and Metal backends and aggressive quantisation, with no compilation step, under the MIT license.
Ollama
The simplest way to pull down an open language model and run it on your own machine, from one command or a desktop app.
Ollama trades MLC LLM's compiler approach for one-command model downloads and a desktop app, with a localhost REST API, but no browser or phone deployment.
mistral.rs
A Rust inference engine for running text, vision and multimodal models locally with an OpenAI-compatible server.
mistral.rs is a Rust engine loading GGUF models behind an OpenAI and Anthropic compatible server, aimed at local servers rather than mobile or browser deployment.
vLLM
High-throughput, memory-efficient inference and serving engine for LLMs.
vLLM focuses on high-throughput serving on Linux GPUs instead of reaching phones and browsers, and also uses the Apache-2.0 license.
LocalAI
Serve language, image and speech models on your own hardware.
LocalAI serves language, image and speech models behind APIs for common AI services on Linux and macOS, without MLC LLM's compilation step or browser target.
LM Studio
A polished desktop app for downloading, running and chatting with local language models, with an OpenAI-compatible server built in.
LM Studio replaces developer tooling with a desktop app built on llama.cpp and MLX with an OpenAI-compatible server, but it is closed source.
MLX LM
A Python package and command-line tool for running and fine-tuning language models on Apple silicon.
MLX LM runs and fine-tunes models only on Apple silicon from the terminal, dropping MLC LLM's cross-GPU, mobile and browser reach.
Foundry Local
Microsoft's tool for downloading and running AI models entirely on your own device.
Foundry Local is Microsoft's tool for on-device models with hardware acceleration and app SDKs on Windows and macOS, but it is not open source.
Similar software
Related functionality, not necessarily a direct replacement.
SGLang
A serving framework for running large language models and multimodal models on your own GPUs.
OpenLLM
A command-line tool that serves open-source LLMs as OpenAI-compatible APIs on your own hardware.
Lemonade
A local AI runtime that serves text, image and speech models through a GUI, CLI and API.
exo
Connects your own computers into a cluster for running large AI models locally.
Hugging Face Hub
A web platform for hosting, finding and sharing machine learning models, datasets and demo apps.