<aside> 🛠

Unified Multimodal Image Generation & Editing

A lightweight 5B-parameter unified multimodal model supporting general image generation, general image editing, reasoning image generation, reasoning image editing, and text rendering, all in a single model

</aside>

What it does

DeepGen 1.0 is a unified multimodal image generation and editing model built on a hybrid VLM + DiT (Diffusion Transformer) architecture. With only 5B parameters (3B VLM + 2B DiT), it integrates five core capabilities in a single model while remaining competitive with or surpassing models 3× to 16× larger. The model is designed to demonstrate that massive scaling is not the only path to high-performance multimodal generation.

Problem it solves

• Lightweight efficiency – Achieves state-of-the-art performance at just 5B parameters, far smaller than comparable unified models (e.g., BAGEL at 14B, Hunyuan-Image-3.0 at 80B)
• Unified capabilities – Combines generation, editing, reasoning generation, reasoning editing, and text rendering in one model, eliminating the need for separate specialized models
• Semantic understanding – Overcomes limitations of lightweight models via Stacked Channel Bridging (SCB), enabling fine-grained semantic control
• Reasoning-aware generation – Supports complex, knowledge-intensive prompts that require multi-step reasoning before generating or editing an image
• Creative workflows – Suitable for design, content creation, and multimodal applications requiring both generation and editing

Input/Output

<aside>

• Input:
  • Text-to-image: Natural language text prompt describing the desired image
  • Image-to-image: One or more reference images + a text instruction for editing or transformation
    • Supports: general editing, style transfer, reasoning-based editing, identity preservation </aside>

<aside>

• Options:
  • Diffusion steps (10 - 50): Diffusion steps control how many refinement iterations the model uses to generate an image (default: 50)
  • Random seed
  • Output image height & width (default: 512×512) </aside>

<aside>

• Output: Generated or edited image

  • Quality: High-fidelity, semantically accurate, fine-grained detail

    

</aside>

Accuracy & Speed

• Quality Metrics:

General Image Generation:

General Image Editing: