The Marketing Model Arena (MMA) is a community-driven platform that ranks large language models (LLMs) based on their performance in marketing-related tasks, particularly copywriting and content creation. It uses a blind A/B voting system where users compare anonymized outputs from different models on specific prompts, such as generating headlines or campaign ideas. Votes contribute to an Elo-based leaderboard that reflects collective preferences for English-language marketing scenarios. This approach provides an objective way to evaluate which models perform better in areas like creativity, relevance, and persuasiveness.

The platform helps users identify suitable LLMs for marketing copywriting by aggregating real-world feedback from comparisons. For example, tasks might involve crafting concise headlines or brainstorming strategies, allowing participants to see strengths in practical applications like ad copy, social media content, or email campaigns. As more votes are added, the rankings become more reliable, offering insights into model performance without requiring individual testing of each option.

MMA is free to use and focuses on community contributions to maintain the leaderboard. It currently supports English tasks and is useful for anyone working with AI in marketing, providing a data-driven reference for selecting models that align with specific needs in content generation and digital marketing.