Open-source image model rivals closed systems on minimal budget

Boogu-Image-0.1 achieves competitive text-to-image generation and editing with only $400K training cost and 208.6 million images.

Independent
Guoxuan Chen · Chufeng Xiao · Haoran Yang · Siyue Xie · Binxiao Huang · Ming Zhang · +27 more
Research Digest··1 min read

In one line

Boogu-Image-0.1 matches or surpasses open-source models using only 208.62 million images and approximately $400K training cost.

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Boogu-Image-0.1 is an open-source family of models, including Base, Turbo, Edit, and Edit-Turbo variants. It supports text-to-image generation, fast inference, instruction-based editing, and bilingual text rendering.

The work demonstrates that strengthening understanding capability through a stronger multimodal encoder, agentic prompt rewriting, improved data quality, and refined training pipelines can substantially enhance generation and editing performance even under highly constrained compute budgets.

Comprehensive evaluations show Boogu-Image-0.1 consistently matches or surpasses other open-source models across standard benchmarks and approaches leading closed-source systems. This is accomplished with only 208.62 million unique images and a theoretical training cost of approximately $400K.

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Research Digest

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