llm-tournament provides a modular, extensible approach for benchmarking large language models. Users define participants (LLMs), configure tournament brackets, specify prompts and scoring logic, and run automated rounds. Results are aggregated into leaderboards and visualizations, enabling data-driven decisions on LLM selection and fine-tuning efforts. The framework supports custom task definitions, evaluation metrics, and batch execution across cloud or local environments.

PromptsLabs is a platform where users can discover and share prompts to test new language models. The community-driven library provides a wide range of copy-paste prompts along with their expected outputs, helping users to understand and evaluate the performance of various LLMs. Users can also contribute their own prompts, ensuring a continually growing and up-to-date resource.