This workflow is designed for Anima 8-step fast anime image generation, focusing on speed, simplicity, and clean visual output. Its main purpose is to help creators generate polished anime-style illustrations much faster than a traditional long-step workflow, while still keeping enough quality for Civitai previews, RunningHub examples, YouTube thumbnails, Bilibili covers, and daily prompt testing.
The workflow uses waiANIMA_v10 as the main Anima generation model, qwen_3_06b_base as the text encoder, and qwen_image_vae as the VAE. It also applies anima-turbo-lora-v0.1 through a model-only LoRA loader. This Turbo LoRA is the core acceleration component of the workflow. Instead of relying on a heavy 30-step or 40-step generation process, the workflow is built around a compact 8-step route, making it much more suitable for rapid iteration.
The canvas is controlled through a resolution node using a 16:9 panorama layout at around 1.0 megapixel. This makes the workflow naturally suitable for wide anime key visuals, cinematic fantasy scenes, horizontal cover images, and video thumbnail-style outputs. The example prompt in the graph is built around an epic anime key visual: a mature anime beauty, fantasy atmosphere, celestial conflict, dramatic lighting, strong character design, and a large-scale background. This kind of prompt is useful for testing whether the accelerated Anima route can still handle composition, character appeal, lighting, and atmosphere under a short sampling setup.
The workflow uses CLIPSetLastLayer, positive and negative prompt encoding, EmptyLatentImage, and ClownsharKSampler_Beta as the main sampling structure. The first sampling pass runs with 8 steps, low CFG, beta-style scheduling, and an acceleration-friendly sampler route. This stage creates the main image quickly from the text prompt. The result is decoded through the Qwen image VAE and saved as the first output.
A second refinement route is also included. After the first latent output is generated, LatentUpscaleBy enlarges the latent by 1.5x, and the workflow sends it into another 8-step sampling pass with reduced denoise. This second pass is useful because it gives the image a stronger final polish without fully restarting the generation. It can improve detail density, line clarity, lighting finish, and overall visual sharpness while preserving the first-pass composition.
The negative prompt is practical and lightweight. It suppresses worst quality, low quality, low-score output, artist names, blur, JPEG artifacts, low resolution, and censored-looking results. This keeps the workflow simple enough for fast use, while still reducing common failure patterns in batch generation.
This workflow is ideal for creators who want a fast Anima setup for anime illustration, prompt testing, key visual drafting, cover image creation, and Civitai showcase production. It is not meant to be a slow maximum-quality graph. Its value is speed: write a prompt, generate quickly, upscale/refine in the second pass, and get a usable anime image with much less waiting. If you want to see how the Turbo LoRA, 8-step sampler, 16:9 canvas, and second-pass latent upscale are connected, watch the full tutorial from the YouTube link above.
⚙️ Try the Workflow Online
👉 Workflow: https://www.runninghub.ai/post/2052343882582634497?inviteCode=rh-v1111
Open the link above to run the workflow directly online and view the generation results in real time.
If the results meet your expectations, you can also deploy it locally for further customization.
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📺 Bilibili Updates (Mainland China & Asia-Pacific)
If you are in Mainland China or the Asia-Pacific region, you can watch the video below for workflow demos and a detailed creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1d8dPBCErN/
I will continue updating model resources on Quark Drive:
👉 https://pan.quark.cn/s/20c6f6f8d87b
These resources are mainly prepared for local users, making creation and learning more convenient.
⚙️ 在线体验工作流
👉 工作流： https://www.runninghub.ai/post/2052343882582634497?inviteCode=rh-v1111
打开上方链接即可直接运行该工作流，实时查看生成效果。
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/BV1d8dPBCErN/
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。