01
Separate the four entry points before comparing features
LiblibAI exposes image generation, video generation, WebUI, ComfyUI, LoRA training, and AI apps in the same navigation. It looks like one long feature list, but the real experience depends on the layer you enter: completing one generation, reusing a model or workflow, managing a local environment, or integrating a process into your own product.
These layers do not form one universal ladder. The web can deliver an image fastest. ComfyUI suits people who need visible relationships between nodes and parameters. The Windows client manages models, launchers, and outputs locally. Open APIs matter when an eligible workflow needs to be called from another application.
02
First use: finish one image before adopting a complex workflow
The official beginner tutorial separates online generation into an input area and a parameter area, then introduces models, prompts, samplers, steps, and dimensions. That is a useful beginner path: learn how inputs affect outputs, then determine whether a problem comes from the prompt, model, or parameters instead of copying a node graph you cannot explain.
For a social visual, concept sketch, or product mood image, the web is often enough. A structured workflow starts paying off when the same task must be repeated, handed between people, or reproduced under controlled conditions.
03
ComfyUI and the local client solve different problems
ComfyUI changes how the process is expressed: models, inputs, controls, and outputs become visible connections, and multi-step operations can be saved. It suits reference control, local processing, batches, and team templates, but more nodes do not automatically produce better results. An unmaintainable graph simply turns short-term experimentation into a long-term burden.
The Windows client addresses deployment and local management. Its official page describes installing the environment, downloading or reusing models, and launching WebUI and ComfyUI together. Hardware wording varies across sections of that page, so do not rely on one remembered VRAM number. Recheck current requirements, available storage, GPU support, and model size before installing.
04
An API is another delivery path, not simply more advanced generation
Open APIs become relevant when generation must serve a website, internal tool, or automated process. The questions change from interface usability to workflow eligibility, usage costs, result retention, retry behavior, and whether the model and source assets permit that use.
Start product integration with one bounded process, such as a fixed-size product background, rather than automating an entire creative workspace. Validate inputs, outputs, errors, and cost records before expanding models and parameters so editorial flexibility is not mistaken for stable service behavior.
05
Finish with credits, hardware, and rights because they change the real cost
Online generation is metered in credits, with model choice and promotions affecting both cost and allowances. Local operation reduces dependence on online credits but adds hardware, storage, environment maintenance, and download time. APIs shift costs toward call volume, retries, and product operations. Compare the total cost of completing the same task, not just the monthly membership price.
The platform also contains community models and workflows, so membership does not prove that every item can be downloaded, used commercially, or called through an API. A production project should retain the exact item, creator or source, license wording at the time, and generation date. People, brands, and client assets require separate input-rights checks.
06
