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AnyPose

lilylilith

Creating poses for Qwen Image Edit (2511) or its variants can be difficult. Even with openpose being baked into the model, it can still look like something is off with the result, such as the depth being incorrect or the pose not fully matching the character, with distortions that you wouldn't expect. Additionally, creating them by hand can take a bit too long, especially if you are going the blender openpose rig route. What if instead you could just skip openpose entirely and write a simple (but albeit lengthy) prompt to copy the pose of any image on your computer? Well, this is what the AnyPose LoRAs attempt to do. Made in mind with the new Qwen Image Edit 2511 lightning LoRA for fast inference, with just a single reference image as a pose guide, you can pilot any image to follow that pose. No control net needed. Use 4-step lightning LoRA for Qwen Image Edit 2511. Set both of the AnyPose LoRA weights (base & helper) strength to 0.7. Upload two images, one with the initial input character, and another with the pose you want copied to the first character. Use the following prompt, "Make the person in image 1 do the exact same pose of the person in image 2. Changing the style and background of the image of the person in image 1 is undesirable, so don't do it. The new pose should be pixel accurate to the pose we are trying to copy. The position of the arms and head and legs should be the same as the pose we are trying to copy. Change the field of view and angle to match exactly image 2. Head tilt and eye gaze pose should match the person in image 2." If additional context is needed (such as clothing that is unseen from the model), prompt it in at the end. Background not staying the same as the initial input image? Append the following to the end "Remove the background of image 2, and replace it with the background of image 1."

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QIE-2511-MP-AnyLight

lilylilith

Lighting is the hardest thing about AI image generation by far. Even if you specify the lighting direction with keywords, the level of control we have for lighting is primitive to say the least. It is very hard to get the desired lighting that you are actually envisioning, not just generic lighting setups like from the left, right, etc, but actual complex lighting setups that are hard to specify in just words. Professionals and people who are serious with getting the right results require it, because currently lighting is for all intents and purposes completely random. You cannot specify the distance the AI generates the light (eg. 40ft away), nor the specific X,Y,Z angle of the light. There have been other attempts to light up a scene, such as Lighting Remap Alpha0.2, which help position lights in various positions. This does help, however, it still falls to the pitfalls mentioned previously since it's based on a 2d canvas. Wouldn't it be better to have some sort of semi real-time lighting setup where you can roughly make sure the character is lit up the way that you want it while not being bound to two-dimensions? Well, this is what this LoRA attempts to do. How is this possible? Well, with a mix of a couple LoRAs (Material Preview style), Trellis2 model generation (or Hunyuan 2.1/3), and Blender, we can have more precise control over the lighting in the scene.

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COST EXPLORER

好模型，也要算好成本。

费用分析

调整月度 Token 用量，直观比较不同模型的预估 API 开支。

每月输入 Token 10 M每月输出 Token 2 M1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价

使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照；不计缓存优惠、阶梯价、推理额外输出与税费，请以来源的当前报价为准。

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选型与常见问题

API 价格应该怎么比较？+

先区分输入、输出和缓存价格，再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费，不能直接与 Token 单价比较。

开放权重，就代表可以免费商用吗？+

不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。

排行榜第一，就是最适合我的模型吗？+

榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本，再选择模型。