This workflow is the active control-oriented Anima Aesthetic 1.1 graph in this batch. It is made for users who want stronger structure control than plain text-to-image while still keeping the Anima anime style. The workflow uses an Anima LLLite control path to inject guidance into the generation process, making it useful for pose, layout, depth-like structure, edge influence, or composition experiments depending on the prepared control input. Compared with the simpler baseline workflow, this one is better when the scene needs a specific body direction, framing, or visual layout.

The inspected graph uses `anima-base-202605-v1.0.safetensors`, Qwen Image CLIP, Qwen Image HDR VAE, and an active `anima-highres-aesthetic-boost.safetensors` LoRA. The control route includes `Anima-LLLite/anima-lllite-any-test-like-v2.safetensors` through AnimaLLLiteApply. The sampling structure uses 30-step passes, with a first pass around CFG 3.0 and a second lower-denoise refinement around 0.55 and CFG around 2.88. A 3:4 resolution selector and 1.5x latent upscale stage are present. The prompt text contains a 16:9 phrase, but the connected size nodes point to 3:4, so this preview follows the actual graph structure rather than the prompt wording.

Main features:

- Control-focused Anima Aesthetic 1.1 workflow
- Active Anima LLLite control injection
- Active highres aesthetic boost LoRA
- Qwen Image CLIP text encoder
- Qwen Image HDR VAE route
- 30-step controlled generation pass observed
- Lower-denoise refinement pass observed
- 3:4 composition support through connected size nodes
- 1.5x latent upscale stage in the graph
- Useful for pose, layout, and composition control tests
- Turbo LoRA is present but bypassed
- Technical copy follows connected nodes, not prompt-only aspect words

Suggested workflow:

Prepare a clean control input first, then write a prompt that supports the same pose and scene rather than fighting it. If the image follows the control too loosely, increase control influence gradually. If it becomes rigid or loses aesthetic quality, reduce control strength and let the refinement pass recover detail. Keep the control image simple when testing new prompts.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2078374978801905666?inviteCode=rh-v1111

If the results meet your expectations, you can later deploy it locally for customization.

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📺 Bilibili Updates (Mainland China & Asia-Pacific)

If you’re in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1xJKB6vEfp/

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⚙️打开下方链接即可在线体验，无需安装。
👉 工作流： https://www.runninghub.ai/post/2078374978801905666?inviteCode=rh-v1111
如果觉得效果理想，你也可以在本地进行自定义部署。

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📺 Bilibili 更新（中国大陆及南亚太地区）

如果你在中国大陆或南亚太地区，可以通过下方视频查看该工作流的实测效果与构思讲解。
📺 B站视频： https://www.bilibili.com/video/BV1xJKB6vEfp/

我会在 夸克网盘 持续更新模型资源：
👉 https://pan.quark.cn/s/20c6f6f8d87b
这些资源主要面向本地用户，方便进行创作与学习。