Pixal3D Image to 3D GLB Asset Workflow

Watch the full video first if you want to understand how this image-to-3D workflow works in practice. The video shows the real launch process, the core node logic, and how to turn a single image into a usable GLB asset directly online.

This ComfyUI workflow is designed for Pixal3D image-to-3D asset generation. Its main purpose is to take a single input image and convert it into a textured 3D model that can be exported as a GLB file. Instead of using a traditional 3D modeling workflow that requires manual sculpting, retopology, UV work, and texture painting, this workflow provides a much faster AI-assisted route for creating a usable 3D asset draft from one image.

The workflow is built around RunningHub Pixal3D nodes. The pipeline starts with RunningHubPixal3DModelLoader, which loads the Pixal3D generation pipe. The loader uses flash_attn as the attention backend and flex_gemm as the sparse convolution backend, giving the workflow a practical acceleration structure for online 3D generation. The input image is loaded through LoadImage, then passed into RunningHubPixal3DImageTo3D as the visual reference for 3D reconstruction.

The core generation node is RunningHubPixal3DImageTo3D. This node receives the Pixal3D pipe and the input image, then generates a 3D asset. The workflow includes parameters for seed control, output resolution, guidance strength, guidance rescale, sampling steps, shape generation, texture generation, mesh scale, camera image resolution, and maximum token count. These settings control how strongly the model follows the image, how the geometry is reconstructed, and how the texture stage is generated.

After the 3D asset is generated, RunningHubPixal3DSaveGLB exports it as a GLB file. The workflow uses a decimation target, texture size, remesh option, and filename prefix. This is important because a raw 3D generation result often needs to be optimized before use. Decimation helps control mesh complexity, texture size controls output texture resolution, and remesh can help produce a cleaner 3D structure for preview or later use.

The workflow also includes Preview3D, allowing users to inspect the generated GLB asset directly inside the workflow environment. This is useful because image-to-3D generation must be checked from multiple viewing angles. A result that looks good from the original camera may still need inspection from the side, back, top, or lower angles. Preview3D makes this process faster and easier.

This workflow is suitable for fast 3D asset prototyping, AI product mockups, stylized object generation, character prop testing, game asset drafts, e-commerce visual experiments, animation previsualization, and 3D concept exploration. It is not meant to fully replace professional 3D modeling, but it can greatly reduce the time needed to create a first 3D asset draft.

Compared with ordinary image generation workflows, this pipeline produces an actual 3D output rather than a flat 2D picture. Compared with traditional 3D production, it is much faster and easier to test. For creators, the biggest value is speed: upload an image, run Pixal3D, export GLB, preview the model, and then decide whether the result is good enough for further refinement in Blender, game engines, product visualization tools, or other 3D software.

Main features:

- Pixal3D image-to-3D generation workflow

- Single image input to 3D asset output

- RunningHubPixal3DModelLoader pipeline loading

- RunningHubPixal3DImageTo3D core generation node

- Shape and texture generation controls

- GLB export through RunningHubPixal3DSaveGLB

- Decimation target and texture size control

- Optional remesh output

- Preview3D model inspection

- Suitable for 3D asset drafts, product mockups, props, and concept models

Suggested workflow:

Prepare a clean input image first. The subject should be clear, centered, and not heavily blocked by complex backgrounds. Upload the image into LoadImage, then run the Pixal3D generation node with the default settings for the first test. After the asset is generated, export it through RunningHubPixal3DSaveGLB and inspect the result in Preview3D. If the shape is too rough, adjust sampling or guidance settings. If the model is too heavy, reduce the decimation target or texture size. Once the GLB result is acceptable, you can import it into Blender, Unity, Unreal Engine, or other 3D tools for further editing, cleanup, rigging, rendering, or production use.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.

👉 Workflow: https://www.runninghub.ai/post/2057792674358452225?inviteCode=rh-v1111

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

🎁 Fan Benefits: Register to get 1000 points + daily login 100 points — enjoy 4090 performance and 48 GB super power!

📺 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/BV1siGb6sEfq/

☕ Support Me on Ko-fi

If you find my content helpful and want to support future creations, you can buy me a coffee ☕.

Every bit of support helps me keep creating — just like a spark that can ignite a blazing flame.

👉 Ko-fi: https://ko-fi.com/aiksk

💼 Business Contact

For collaboration or inquiries, please contact aiksk95 on WeChat.

⚙️打开下方链接即可在线体验，无需安装。

👉 工作流： https://www.runninghub.ai/post/2057792674358452225?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。

🎁 粉丝福利： 注册即送 1000 积分，每日登录 100 积分，畅玩 4090 体验 48 G 超级性能！

📺 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/BV1siGb6sEfq/

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。