3 projects for "complex" with 2 filters applied:

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  • 1
    GLM-Image

    GLM-Image

    GLM-Image: Auto-regressive for Dense-knowledge and High-fidelity Image

    GLM-Image is an open-source generative AI model designed to create high-fidelity images from text prompts using a hybrid architecture that combines autoregressive semantic understanding with diffusion-based detail refinement. It excels at generating images that include complex layouts and detailed text content, making it especially useful for posters, diagrams, info-graphics, social media graphics, and visual content that requires precise text placement and semantic alignment. Because it blends linguistic reasoning with image synthesis, GLM-Image produces visual outputs where semantic relationships and textual accuracy are prioritized alongside artistic style and realism, and its model structure enables it to handle dense visual knowledge tasks that challenge many pure diffusion models. ...
    Downloads: 7 This Week
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  • 2
    Z-Image

    Z-Image

    Image generation model with single-stream diffusion transformer

    Z-Image is an efficient, open-source image generation foundation model built to make high-quality image synthesis more accessible. With just 6 billion parameters — far fewer than many large-scale models — it uses a novel “single-stream diffusion Transformer” architecture to deliver photorealistic image generation, demonstrating that excellence does not always require extremely large model sizes. The project includes several variants: Z-Image-Turbo, a distilled version optimized for speed and...
    Downloads: 20 This Week
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  • 3
    HunyuanImage-3.0

    HunyuanImage-3.0

    A Powerful Native Multimodal Model for Image Generation

    HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter...
    Downloads: 2 This Week
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