Bagel: The Open-Source ChatGPT Rival With Built-In Images

Today, I want to share my insights on Bagel, an exciting fully open-source multimodal AI model that functions similarly to ChatGPT but with some distinctive capabilities. What makes Bagel particularly interesting is not just its ability to understand images but also to generate them natively—all within a fully open-source framework. 🥯

What Is Bagel and Why It Matters

Bagel is a foundation model with 7 billion active parameters (14 B total) developed by ByteDance and released under an Apache 2.0 license. While you shouldn’t expect performance matching ChatGPT’s GPT-4o, Bagel represents a significant milestone in the AI landscape: the first truly open-source model that can both understand and generate images natively.

This matters because, until now, unified multimodal AI models capable of bidirectional text-and-image processing have been offered only through closed platforms (e.g., OpenAI’s ChatGPT, Google’s Gemini, xAI’s Grok). Bagel brings this technology into the open-source community, allowing developers and businesses to modify, redistribute, and build upon it freely.

✨ At Promptus, we’re excited about the customization possibilities this opens up for our visual workflows. Incorporating a fully modifiable multimodal model into Cosyflows could significantly enhance what our users can create.

How Bagel Compares to ChatGPT’s Image Capabilities

In my testing, Bagel’s image understanding is impressive for an open-source model:

• Detailed understanding: When presented with complex visuals, Bagel can provide descriptive captions and even imaginative backstories based on visual cues.
• “Thinking mode”: Exposes the model’s internal reasoning steps, often yielding more creative and coherent narratives.

Where Bagel truly differentiates itself from ChatGPT is in its approach to image generation:

1. Character consistency
   Bagel can maintain consistent characters across multiple generated images—valuable for storyboarding or sequential visuals.
2. Image editing
   Upload an image and ask for specific modifications; Bagel attempts to preserve key elements of the original while applying changes.
3. Spatial understanding
   Bagel shows rudimentary 3D reasoning: rotating objects in uploaded images or “navigating” through generated scenes.

However, ChatGPT currently holds an edge in sheer image quality and prompt interpretation. In comparative tests with identical prompts, ChatGPT’s outputs tend to be higher-fidelity, more detailed, and more accurately aligned with user intent.

The Potential for Customization Beyond ChatGPT

What excites me most about Bagel is its future potential. Unlike ChatGPT, Bagel can be fine-tuned, distilled, and deployed anywhere—opening possibilities that closed systems cannot match. 🚀

• Specialized fine-tuning: At Promptus, we’re exploring fine-tuned Bagel variants optimized for specific creative tasks (e.g., cinematic scenes with consistent characters, product visualization tailored to brand guidelines).
• Deep MoMM integration: Bagel’s open architecture may allow deeper integration into our Model Multi-Modality (MoMM) system, letting users combine Bagel with other AI models within a single workflow for unique outputs.
• User-controlled parameters: Bagel’s demo interface often offers explicit toggles for image-generation settings—CFG scales, sampling steps, toggling “thinking mode”—giving users granular control not available in ChatGPT’s UI.

When to Use Bagel vs. ChatGPT

• Casual users / general-purpose tasks: ChatGPT remains the superior immediate choice for high-fidelity, polished text-and-image generation.
• Developers / businesses / platforms: Bagel’s real value lies in freedom: ability to customize, fine-tune, and deploy without licensing restrictions. Over time, specialized Bagel variants may outperform general-purpose models in targeted applications.

💡 The emergence of open-source multimodal models like Bagel signals an exciting shift: while closed systems maintain lead in off-the-shelf quality, open alternatives enable innovation through customization.

Implications for Promptus and Creative Workflows

At Promptus, we aim to incorporate the best AI technologies into our no-code studio, making them accessible through visual workflows:

• Cosyflows + Bagel: Imagine a node in Cosyflows that leverages Bagel for unified text-and-image tasks, editable and fine-tunable by advanced users.
• Hybrid pipelines: Use Bagel for certain image-understanding or generation steps, then pass outputs to other specialized models (e.g., Stable Diffusion variants, video models) within one visual workflow.
• User empowerment: Providing optional Bagel integration gives creators choice: use a fully open model they can host/fine-tune, or default to a closed-service model for ease-of-use.

If you’re curious how these technologies can enhance your creative process, sign up at https://www.promptus.ai and choose Promptus Web (browser-based) or Promptus App (for heavier local workloads).

The Future of Open-Source ChatGPT Alternatives

While ChatGPT may maintain its lead in general-purpose applications, Bagel’s open license and multimodal capabilities open a world of possibilities for specialized workflows:

• Custom deployments: Organizations can host Bagel on-premise or in custom cloud configurations, ensuring data privacy or low-latency inference.
• Community-driven improvements: Developers can contribute fine-tuning datasets, novel adapters/plugins, or upstream model improvements, accelerating Bagel’s capabilities.
• Niche-focused variants: Specialized Bagel forks could excel in domains like medical imaging captioning/generation, architectural design mockups, or educational content with integrated visual explanations.

As creators and developers, we’re just beginning to explore what these open-source multimodal models can do when tailored to specific needs.

Conclusion

Bagel represents a meaningful step in democratizing multimodal AI: an open-source ChatGPT-like model with native image understanding and generation. While it may not yet match ChatGPT’s fidelity out-of-the-box, its open architecture unlocks future innovation through customization, fine-tuning, and integration into platforms like Promptus.

For immediate high-quality results, closed platforms remain strong. But for those seeking freedom to build, adapt, and deploy tailored AI solutions, Bagel is an exciting frontier.

🔗 Explore Promptus: Bring powerful AI into no-code visual workflows—visit https://www.promptus.ai to get started.

The AI landscape is shifting toward greater openness and modularity. As we embrace open-source multimodal models like Bagel, we can craft bespoke creative tools that align precisely with our visions and requirements. The best is yet to come. 🎉