Get high-performance AI model inference with xllm, ideal for startup founders working with large language models, backed by 1.4k+ GitHub stars
1,468 stars256 forksC++Quality 8/10Updated 7/13/2026100% free ยท open source
What it does
xllm provides high-performance inference for large language models, enabling fast and efficient processing of AI workloads
Install / run
git clone https://github.com/xLLM-AI/xllm.git
When to use it
โขYou need to deploy large language models in a production environment with strict latency requirements
โขYour startup relies on real-time natural language processing for tasks like sentiment analysis or text classification
โขYou want to optimize the performance of your AI models on diverse hardware accelerators
Quick start
1Build the xllm engine using the command 'mkdir build && cd build && cmake .. && make -j'
2Prepare your model by converting it to the xllm format using the 'xllm_convert' tool
3Create a configuration file 'config.json' to specify the model and accelerator settings
4Run the xllm inference engine using the command 'xllm_infer -c config.json -m your_model.xllm'
5Use the 'xllm_benchmark' tool to evaluate the performance of your model on different hardware accelerators
Ready-to-paste prompt
xllm_infer -c config.json -m your_model.xllm -i 'What is the capital of France?'
Heads up: Ensure you have the necessary dependencies installed, including CMake and a compatible C++ compiler, and that your model is compatible with the xllm format
Saves to your device
Topics
deepseek
glm
inference
inference-engine
large-language-models
llm-inference
qwen
What's inside โ free to inspect
No purchase needed
Read the entire source before you build โ unlike paid marketplaces that hide it behind a buy button.