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README.md
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# 🥯 BAGEL • Unified Model for Multimodal Understanding and Generation
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> We present **BAGEL**, an open‑source multimodal foundation model with 7B active parameters (14B total) trained on large‑scale interleaved multimodal data. BAGEL outperforms the current top‑tier open‑source VLMs like Qwen2.5-VL and InternVL-2.5 on standard multimodal understanding leaderboards, and delivers text‑to‑image quality that is competitive with strong specialist generators such as SD3.
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Moreover, BAGEL demonstrates superior qualitative results in classical image‑editing scenarios than the leading open-source models. More importantly, it extends to free-form visual manipulation, multiview synthesis, and world navigation, capabilities that constitute "world-modeling" tasks beyond the scope of previous image-editing models.
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Below is a showcase of BAGEL's qualitative performance.
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This repository hosts the model weights for **BAGEL**. For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/bytedance-seed/BAGEL).
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| Janus-Pro-7B | 0.80 |
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| **BAGEL** | **0.88** |
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### 3. Image Editing
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## License
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BAGEL is licensed under the Apache 2.0 license. It is finetuned from [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) and [siglip-so400m-14-980-flash-attn2-navit](https://huggingface.co/HuggingFaceM4/siglip-so400m-14-980-flash-attn2-navit) model, and uses the [FLUX.1-schnell VAE model](https://huggingface.co/black-forest-labs/FLUX.1-schnell), all under Apache 2.0.
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<p align="left">
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<img src="https://lf3-static.bytednsdoc.com/obj/eden-cn/nuhojubrps/banner.png" alt="BAGEL" width="480"/>
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</p>
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# 🥯 BAGEL • Unified Model for Multimodal Understanding and Generation
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> We present **BAGEL**, an open‑source multimodal foundation model with 7B active parameters (14B total) trained on large‑scale interleaved multimodal data. BAGEL outperforms the current top‑tier open‑source VLMs like Qwen2.5-VL and InternVL-2.5 on standard multimodal understanding leaderboards, and delivers text‑to‑image quality that is competitive with strong specialist generators such as SD3.
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Moreover, BAGEL demonstrates superior qualitative results in classical image‑editing scenarios than the leading open-source models. More importantly, it extends to free-form visual manipulation, multiview synthesis, and world navigation, capabilities that constitute "world-modeling" tasks beyond the scope of previous image-editing models.
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This repository hosts the model weights for **BAGEL**. For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/bytedance-seed/BAGEL).
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| Janus-Pro-7B | 0.80 |
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| **BAGEL** | **0.88** |
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### 3. Image Editing
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| Model | GEdit-Bench-EN (SC) ↑ | GEdit-Bench-EN (PQ) ↑ | GEdit-Bench-EN (O) ↑ | IntelligentBench ↑ |
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| ------------- | --------------------- | --------------------- | ------------------- | ------------------ |
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| Step1X-Edit | 7.09 | 6.76 | **6.70** | 14.9 |
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| Gemini-2-exp. | 6.73 | 6.61 | 6.32 | **57.6** |
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| **BAGEL** | **7.36** | **6.83** | 6.52 | 44.0 |
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| **BAGEL+CoT** | – | – | – | 55.3 |
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## License
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BAGEL is licensed under the Apache 2.0 license. It is finetuned from [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) and [siglip-so400m-14-980-flash-attn2-navit](https://huggingface.co/HuggingFaceM4/siglip-so400m-14-980-flash-attn2-navit) model, and uses the [FLUX.1-schnell VAE model](https://huggingface.co/black-forest-labs/FLUX.1-schnell), all under Apache 2.0.
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