SD3模型到底如何？StableDiffusion3全面评测！如何使用ComfyUI遍历题词 | 模型？（附赠测试工作流）！ #aigc #stablediffusion3

The video begins with an introduction to the newly open-sourced SD third-generation model, highlighting its enhanced architecture based on SDXL with improved VAE decoding and better integration of prompts and elements. The host also discusses ComfyUI's batch processing operations and guides viewers to the SD official website, explaining the differences in the new model, including the addition of a text encoder and the increase in training data to 2 billion parameters. The video then navigates to Huggingface's website to explain the various model versions available, focusing on the new T5XXL model with three CLIP encodings and the different precision options provided, such as FP16 and 8-bit precision. The host also addresses the system requirements for running these models, mentioning the need for at least 12GB of VRAM and the potential use of virtual memory for lower-end systems.

This paragraph delves into the specifics of different model variants available on Huggingface, the absence of CLIP encoding in certain models, and the necessity to download additional CLIP models for those without. It also explores the concept of negative prompting, explaining how the absence of prompt intensity can lead to a 'zeroing out' effect in the generated images. The host discusses the timing settings for negative prompts and how they are merged to create a linear transition effect, ultimately reducing the negative prompt's impact. Additionally, the video touches on the sampling algorithms and model pipelines in SD3, suggesting that while they are not the most critical components, they do offer some room for optimization.

The host proceeds to test the SD3 model using official prompts, noting the model's 10GB size which includes three CLIP models, eliminating the need for separate downloads. The video showcases the sampling parameters provided by the model and the host's attempt to generate an image, commenting on the slightly 'greasy' appearance of the generated face. Adjustments are made to the CFG value and the sampling method, with the host trying different schedulers and model algorithms to achieve a more desirable result. The video emphasizes the importance of following the negative prompt approach for better image quality and provides a comparison between different work flows, such as basic, prompt强化, and upscale.

The paragraph introduces the concept of dynamic prompts for image iteration, mentioning a plugin called 'Dynamic' that facilitates the use of wildcards in prompts. The host guides viewers on how to install the plugin and use it to generate images with varying styles and elements by referencing different text files containing prompt cards. The video also highlights the resources available on the Lib website for downloading prompt cards and models, emphasizing the convenience and speed of accessing these resources for users in China.

The host discusses the process of batch processing in ComfyUI, explaining how to use the FIZZ node for batch generation and the challenges of integrating dynamic prompts into the batch process. The video demonstrates how to set up a batch process using string concatenation and frame nodes to generate multiple images with different prompts. Additionally, the host compares three different models: SDXL, SD3, and Cascade, using a macro prompt plugin to generate a variety of images and assess the strengths and weaknesses of each model in terms of style and detail.

In this section, the host fine-tunes the SD3 model by adjusting weights and testing it with different prompts, including landscapes and portraits. The video compares the results with SDXL and Cascade models, noting that while SDXL shows better style representation, SD3's outputs are more generic. The host also experiments with various themes and styles, such as watercolor and anime, to see how SD3 handles different artistic interpretations and discusses the potential reasons for the discrepancies in image quality.

The final paragraph wraps up the video with a test of the online generation feature on the Lib website using the SD3 model. The host compares the results with local generation and discusses the potential reasons for any differences observed. The video concludes with an invitation for viewers to share their experiences and optimizations in the comments section and to join a community group for further discussion and support. The host also hints at future content that will explore more about the models and their applications.