hugging face has launched inference providers for openclaw, enabling users to access open source models easily. this allows developers to transition their agents from closed models to open alternatives hosted on hugging face. users can either use the hosted models for quick access or run models locally for more control and privacy.
for game developers, this means you can keep your agents running without incurring additional API costs. if you choose to use hugging face inference providers, you will need to create an API token and configure it in your openclaw setup. alternatively, running models locally with llama.cpp provides full control and eliminates API fees.
if you opt for local setup, ensure your hardware meets the model requirements. you can install llama.cpp and start a local server to run your chosen model. this setup allows for experimentation without the constraints of rate limits. consider using models like unsloth/Qwen3.5-35B-A3B or zai-org/GLM-5 for your projects.
make sure to verify that your local server is running correctly by checking the model status via a simple curl command. this will help you confirm that your setup is functional before proceeding with development.