Playground v2.5 introduces three key insights to enhance aesthetic quality in text-to-image generation. First, it improves color and contrast by using a more principled noise schedule, such as the EDM framework, which reduces muted colors and enhances vividness. Second, it addresses the challenge of generating images across various aspect ratios by balancing the dataset and refining the training process to ensure consistent output. Third, it aligns model outputs with human preferences, focusing on human-centric details like facial features, lighting, and textures. Playground v2.5 outperforms state-of-the-art models like SDXL, DALL·E 3, and Midjourney 5.2 in aesthetic quality, as demonstrated through user studies and benchmarking. The model is open-sourced and available on HuggingFace, with extensions for popular tools like A1111 and ComfyUI. It aims to provide a high-quality, versatile text-to-image generation system that aligns with human preferences and produces realistic, visually compelling images. The model's performance is validated through extensive evaluations, including user studies and automatic benchmarks like MJHQ-30K, which show significant improvements in aesthetic quality across various categories. Playground v2.5 represents a significant step forward in text-to-image generation, offering a robust solution for both research and practical applications.Playground v2.5 introduces three key insights to enhance aesthetic quality in text-to-image generation. First, it improves color and contrast by using a more principled noise schedule, such as the EDM framework, which reduces muted colors and enhances vividness. Second, it addresses the challenge of generating images across various aspect ratios by balancing the dataset and refining the training process to ensure consistent output. Third, it aligns model outputs with human preferences, focusing on human-centric details like facial features, lighting, and textures. Playground v2.5 outperforms state-of-the-art models like SDXL, DALL·E 3, and Midjourney 5.2 in aesthetic quality, as demonstrated through user studies and benchmarking. The model is open-sourced and available on HuggingFace, with extensions for popular tools like A1111 and ComfyUI. It aims to provide a high-quality, versatile text-to-image generation system that aligns with human preferences and produces realistic, visually compelling images. The model's performance is validated through extensive evaluations, including user studies and automatic benchmarks like MJHQ-30K, which show significant improvements in aesthetic quality across various categories. Playground v2.5 represents a significant step forward in text-to-image generation, offering a robust solution for both research and practical applications.