Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget
We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turbo variants. It delivers competitive performance in high-quality text-to-image generation, fast inference, instruction-based editing, and bilingual (Chinese-English) text rendering. Closed-source multimodal systems like Nano-Banana-Pro and GPT-Image-2 achieve strong performance through system-level integration rather than a single model, yet their internal practices remain largely undisclosed. In this work, we demonstrate that strengthening the understanding capability of the system, through a stronger multimodal encoder, agentic prompt rewri...
| Authors | Guoxuan Chen, Chufeng Xiao, Haoran Yang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 July 2026 |
| Last updated at source | 18 July 2026 |
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- Boogu/Boogu-Image-0.1-EditModel · cited by
- Boogu/Boogu-Image-0.1-TurboModel · cited by
- Boogu/Boogu-Image-0.1-Edit-TurboModel · cited by
- Boogu/Boogu-Image-0.1-BaseModel · cited by
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