# Bagel vs ModelScope Bagel records 7,329 monthly visits with -27.5% month-over-month growth and Free pricing. ModelScope records 3,085,423 monthly visits with +5.1% growth and Free pricing. | Metric | [Bagel](https://openaitools.app/tool/bagel) | [ModelScope](https://openaitools.app/tool/modelscope-community) | | :--- | :--- | :--- | | Website URL | https://bagel-ai.org | https://www.modelscope.cn | | Categories | Open Source AI Models, AI Models, AI Image Generator, AI Chatbot | Open Source AI Models, AI Models, AI Developer Tools, Large Language Models (LLMs) | | Pricing Model | Free | Free | | Monthly Visits | 7,329 | 3,085,423 | | MoM Growth Rate | -27.5% | +5.1% | | Primary Market | United States | China | | Direct Visits | 2,868 | 2,108,104 | | Review Score | 4.6 | 4.5 | | Saved Count | 1 | 0 | | Supported Platforms | Website | Website | ## Bagel BAGEL is an open-source unified multimodal model released on May 20, 2025 by a research team led by Chaorui Deng, Deyao Zhu, Kunchang Li, Chenhui Gou, Feng Li and colleagues. Its goal is to deliver functionality comparable to proprietary multimodal systems such as GPT-4o and Gemini 2.0, but in an open form that anyone can fine-tune, distill and deploy. Rather than stitching a separate vision model to a separate image generator, BAGEL is natively multimodal from pre-training onward. The model handles image and text inputs and outputs in a mixed format, so the same system can reason about a picture, hold a conversation, generate photorealistic imagery, edit an existing image, transfer style, navigate a 3D environment or predict future video frames. Architecture-wise, BAGEL adopts a Mixture-of-Transformer-Experts design with two encoders capturing pixel-level and semantic-level features, trained via a Next Group of Token Prediction objective on trillions of interleaved language, image, video and web tokens. The project publishes benchmark comparisons against open models such as Janus-Pro-7B, Emu3-8B, TokenFlow-XL-13B and BLIP3-o-8B. BAGEL reports strong scores on understanding benchmarks like MME-P, MMBench, MMMU and MMVet, and leads the published generation table with an overall score of 0.88 across single-object, two-object, counting, color, position and color-attribute tasks. The team also documents emergent behaviour, noting that complex intelligent editing appears only after foundational understanding and generation skills are established. **Pricing & Plans:** Free and open source. The project publishes the model for fine-tuning, distillation and deployment; there is no paid tier listed on the project page. - **Unified understanding and generation:** A single model accepts mixed image and text inputs and produces mixed image and text outputs for reasoning, conversation and generation. - **Intelligent image editing:** Pre-training on interleaved video clips lets BAGEL preserve identities and fine detail while performing edits that go beyond basic manipulation. - **Style transfer and composition:** BAGEL transforms images between styles and worlds using minimal alignment data, and composes new scenes across turns. - **Video-derived navigation:** By learning from real-world video, the model can navigate varied environments including painted and sci-fi worlds. - **Thinking mode:** A built-in reasoning mode expands short prompts into detailed, logically consistent visual outputs. **Strengths:** Open source and freely deployable, with no licensing fee on the project site; One architecture covers understanding, generation, editing and navigation; Strong published scores against comparable open multimodal models; Explicit thinking mode improves prompt fidelity for complex edits [Profile (Markdown)](https://openaitools.app/tool/bagel.md) ## ModelScope ModelScope, also known as the Magic Model community, is an open-source AI model and dataset hub built and maintained with Alibaba. It gathers models for natural language processing, computer vision, speech, multimodal generation, and more, letting researchers and developers browse, download, and evaluate them in one place. Each model typically ships with documentation, a model card, and an interactive online demo so you can try it directly in the browser before installing anything. Beyond hosting files, ModelScope functions as a full model-as-a-service workspace. Users get free online notebooks with GPU and CPU resources for training and fine-tuning, plus hosted inference endpoints and a Python library that integrates with common deep learning frameworks. Community features such as model collections, benchmarks, competitions, and discussion boards make it a social hub as much as a repository. The platform is free to use, with compute credits and hosted serving tied to account usage. Its close association with Alibaba Cloud means it also serves as a practical gateway for teams who want to move from experimentation to production deployment within a familiar cloud ecosystem. **Pricing & Plans:** Free to use. Browsing, downloading models and datasets, and running online demos are free; free GPU/CPU notebook credits and hosted inference are available, with additional cloud resources tied to Alibaba Cloud services. - **Model & Dataset Hub:** Browse and download thousands of pretrained models and datasets across NLP, vision, audio, and multimodal tasks. - **One-click Online Demos:** Try models directly in the browser through hosted inference demos without local setup. - **Free Notebook Compute:** Run training and fine-tuning in cloud notebooks with complimentary GPU and CPU resources. - **Python Library & SDK:** Integrate ModelScope models into your own pipelines using the official Python package and APIs. - **Community & Benchmarks:** Join competitions, publish model cards, and compare results through community benchmarks and leaderboards. **Strengths:** Huge, free catalog of models and datasets; Built-in online demos require no installation; Complimentary GPU/CPU notebook compute; Strong integration with Alibaba Cloud for scaling **Limitations:** Much of the documentation is Chinese-first; Hosted features may require an account and regional access; Interface can feel dense for newcomers [Profile (Markdown)](https://openaitools.app/tool/modelscope-community.md) ## Frequently Asked Questions ### How do Bagel and ModelScope compare in monthly traffic? Bagel has 7,329 monthly visits, while ModelScope has 3,085,423. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Bagel has a month-over-month growth rate of -27.5%; ModelScope has +5.1%. ### How does pricing compare? Bagel: Free. Free and open source. The project publishes the model for fine-tuning, distillation and deployment; there is no paid tier listed on the project page. ModelScope: Free. Free to use. Browsing, downloading models and datasets, and running online demos are free; free GPU/CPU notebook credits and hosted inference are available, with additional cloud resources tied to Alibaba Cloud services. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Hugging Face](https://openaitools.app/tool/hugging-face) | 31,232,542 | +0.1% | Freemium, Paid | The global standard open-source AI hub offering vastly larger model and dataset repositories than ModelScope. | [.md](https://openaitools.app/tool/hugging-face.md) | | 2 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Convenient API gateway for multi-model access, but does not provide ModelScope's open-source model repository or dataset hosting. | [.md](https://openaitools.app/tool/openrouter-ai.md) | | 3 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Streamlined local CLI runtime for running LLMs, but lacks ModelScope's web-based model hosting and dataset discovery. | [.md](https://openaitools.app/tool/ollama.md) | | 4 | [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | +12.8% | Freemium | Superior community hub specifically for generative image and media models, but lacks ModelScope's broad NLP and code support. | [.md](https://openaitools.app/tool/civitai.md) | | 5 | [MiniMax Image-01](https://openaitools.app/tool/minimax-image-01) | 5,253,734 | -13.2% | Contact for Pricing | MiniMax's open-weight model for turning prompts into images | [.md](https://openaitools.app/tool/minimax-image-01.md) | | 6 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Google's family of lightweight, open-weight AI models | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) | | 7 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Robust cloud infrastructure for running open-source models via API, but lacks ModelScope's community-driven model discovery and demo workspace. | [.md](https://openaitools.app/tool/together-ai.md) | | 8 | [Tencent Hunyuan](https://openaitools.app/tool/tencent-hunyuan-large-model) | 1,485,463 | -1.2% | Contact for Pricing | Tencent's multimodal foundation-model family for text, vision, image and speech | [.md](https://openaitools.app/tool/tencent-hunyuan-large-model.md) | | 9 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Run, fine-tune, and deploy machine learning models with one line of code | [.md](https://openaitools.app/tool/replicate-ai.md) | | 10 | [Agnes AI](https://openaitools.app/tool/agnes-ai) | 902,184 | -25.8% | Freemium | One free API for text, image, and video AI models | [.md](https://openaitools.app/tool/agnes-ai.md) | --- Source: https://openaitools.app/compare/bagel-vs-modelscope-community More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)