Navigating the Open-Source Model Ecosystem: An Empirical Study of Creator Practices in Artistic Image Generation

2026-07-11

AI Summary

This study addresses the lack of systematic understanding regarding creators’ usage patterns of base and fine-tuned models—such as LoRA adapters—in the current open-source image generation ecosystem. The authors construct a large-scale dataset comprising six million generated images along with their associated metadata, enabling the first empirical analysis of how 22.4K base models and 154K LoRA models are combined and utilized in real-world creative workflows. Through data mining, metadata analysis, and log correlation, the research uncovers distinctive strengths and inherent challenges within this ecosystem. These findings provide empirical grounding for enhancing its sustainability and innovation potential, while the publicly released high-quality dataset supports further community engagement and academic inquiry.

Abstract

The open-sourcing of powerful image generation models has created a vibrant ecosystem where creators curate and combine a vast array of community-contributed models. This practice stands in sharp contrast to using closed-source tools like Midjourney. Yet, little is known about these emerging creative workflows. To bridge this gap, this paper presents the first large-scale empirical study of creator model usage behavior within this open-source image generation ecosystem. We construct a novel dataset of 6 million images with their embedded generation metadata -- a detailed recipe of the creation process, including the models used and the prompts. By linking the usage of 22.4K base models and 154K LoRA models to the images, our findings underscore the ecosystem's unique strengths and its inherent obstacles. This provides valuable insights for making this ecosystem more sustainable and innovative. Moreover, we make our dataset publicly available, providing creators with practical references for producing better artworks and researchers to facilitate further studies.

Problem

• open-source models
• image generation
• creator practices
• model usage
• creative workflows

Innovation

• open-source image generation
• empirical study
• model usage behavior
• generation metadata
• LoRA models