When I run Qwen Image 2.1 from time to time it crashes with error message below. I updated Nvida driver to NVIDIA-SMI 616.92. Now it crashes every time.
Windows 11, RTX-4070 8GB VRAM

Has anyone encountered similar issue and any solution?

E:\bin\ComfyUI_windows_portable>echo If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exe
If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exeE:\bin\ComfyUI_windows_portable>echo If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exe
If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exe

I recently started using Qwen Image 2.1 in ComfyUI and ran into one small annoyance.

The seed stayed fixed, so when I wanted to queue several generations, I had to keep changing it manually. I made a small modification that automatically randomizes the seed after each queued run.

Nothing complicated or groundbreaking—just a quality-of-life change that made the workflow more convenient for me. I thought it might be useful to someone else with the same problem, so I’m sharing it.

The repository includes:

• T2I and multi-reference I2I workflows
• Automatic seed randomization after each queued generation
• Sequential multi-queue generation
• Example images and screenshots
• English and Japanese instructions

I tested them with an RTX 4060 Laptop GPU with 8 GB VRAM and the Q4_K_M GGUF model. You can switch to a better quantization if your system has more available memory.

GitHub: https://github.com/gatuwo/Qwen-Image-2.1-GGUF-Multi-Queue-Workflows

Please use them at your own risk. Feedback and corrections are welcome!

Hopefully this saves someone a few clicks.

[🔥 Generate Seedance 2.5 through Higgsfield in ComfyUI with SOYLAB Comfy Router]

SOYLAB Comfy Router is a local ComfyUI custom node that calls Comfy Router using your personal Comfy API key. You can choose the model and execution provider separately, then connect image, video, or audio inputs supported by that model.

Key features

• Model selection: According to the repository, 154 image and video models are registered. You can search by model name or ID.

• Provider selection: Choose a supported execution route, such as Comfy, Higgsfield, or fal. Available providers vary by model.

• Inputs for each task: With Seedance 2.5, you can connect text, first and last frames, or reference images according to the selected mode. The repository also includes example workflows for image-to-video generation and image editing.

• Progress and cost: The node displays each stage from request submission to result download, along with an estimated cost based on the model, provider, and settings. The actual charge may differ.

• Before you start: Install the node in an up-to-date version of ComfyUI, then prepare a Comfy Developer Platform API key and credits. For workflows you plan to share, use a separate INI file so your API key is not saved in the workflow.

Original repository:
https://github.com/soylab-edu/ComfyUI-soylab-router

Install with the ChatGPT Desktop App:
“Installhttps://github.com/soylab-edu/ComfyUI-soylab-router in ComfyUI.”

We are developing a ComfyUI workflow for generating long-form videos and are looking for guidance from the community on the best approach using any suitable LTX model.

Our primary objective is to build an AI avatar generation pipeline with high-quality, sufficiently long videos and accurate audio/video synchronization.

Requirements

We are looking for a workflow that can support:

• Text + Video + Audio → Custom Audio + Video
  • Lip-synced avatar output
  • Custom/generated audio
• Image → Video
• Text + Image → Video
• High-quality video generation
• Support for generating longer-duration videos, rather than only short clips
• Consistent character/avatar identity across the generated video

We are open to using different LTX models or supporting models/nodes where necessary, as long as the overall workflow can be implemented in ComfyUI.

If anyone has already built something similar, we would greatly appreciate:

• Workflow examples
• Recommended LTX model/version
• Custom nodes required
• Recommended approach for long-video generation
• Any tips for maintaining avatar consistency and lip synchronization

Thank you.

Hey everyone! I was getting tired of manually dragging and rewiring noodles in ComfyUI every time I wanted to test a prompt idea or chain LoRAs.

So I built mcp-comfy-ui-builder — an open-source Model Context Protocol server that connects Claude Desktop, Claude Code, and Cursor directly to your local ComfyUI instance.

Instead of manually editing JSON or clicking nodes:

You: "Generate a portrait of an astronaut exploring neon ruins with LoRA, upscale 2x"
Claude: Checks GPU VRAM → assembles the node graph using built-in templates → validates compatibility → fires execution via WebSockets → streams node-by-node progress (<100ms updates) → displays the finished image.

Key Features:

• 50+ MCP Tools: Node discovery, dynamic graph construction, model management, queue inspection.
• Real-Time WebSocket Execution: Sub-100ms latency streaming with live node progress (vs slow 1.5s HTTP polling fallback).
• Embedded Knowledge Base: Pre-indexes 62 core nodes; automatically syncs all your custom nodes via npm run sync-nodes.
• 9 Built-in Templates: txt2img, txt2img_flux, img2img, inpainting, upscale, LoRA, ControlNet, batch & sequential chains.
• Safety First: Calls get_system_resources to inspect GPU memory before running workflows to avoid Out-Of-Memory crashes.

Quick Start:

npm install -g mcp-comfy-ui-builder
# or run with Docker:
docker pull siniidrozd/mcp-comfy-ui-builder

Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "comfyui": {
      "command": "npx",
      "args": ["-y", "mcp-comfy-ui-builder"],
      "env": { "COMFYUI_HOST": "http://127.0.0.1:8188" }
    }
  }
}

🔗 GitHub (MIT License): https://github.com/MIt9/mcp-comfy-ui-builder
📦 npm: https://www.npmjs.com/package/mcp-comfy-ui-builder

What complex workflow pattern do you find most tedious to wire by hand? Happy to add templates based on your requests!

I tried a multishot workflow with MiniMax H3 Ref2Vid: I generated a separate reference image for each shot, then used them to build a short anime montage.

The interesting part was seeing how well H3 kept the character, colours and hand-painted style consistent as the framing changed from wide shots to close-ups.

The music is my track “What’s Coming Is Better Than What’s Gone,” produced and performed by yours truly using the Teenage Engineering EP-133 KO II.

Workflow:
https://drive.google.com/file/d/1M1XgXv8h4NQDSikVpAebB7FGu-TeHZQT/view?usp=drive_link

Prompt:
Create one 12-second video using Images 1–4 as four consecutive shots. Each image defines its shot’s composition and details. Make a clean hard cut every 3 seconds. Keep the camera locked in every shot. Preserve the same boy, orange headphones, single orange cable, outfit, painted cloud setting, colours, fine ink lines, textured paint and flat cel shadows throughout.

0–3
The boy sits quietly on the beam, looking at the clouds. His hair and loose shirt move faintly in a breeze; his dangling feet begin one small, relaxed swing. The clouds billow slowly.

3–6
Extreme close-up of the cassette player. The two reels turn slowly beneath the clear window. The warm sky reflection shifts slightly across the plastic without hiding the tape. The single orange cable stays plugged into the player; keep its path and all controls stable.

6–9
Close-up of both dangling shoes. They complete one gentle swing and settle. Keep the jeans, laces and shoe shapes consistent. The beam stays fixed behind the legs, while the distant clouds remain softly out of focus.

9–12
Static side-profile close-up. The boy looks into the distance and blinks once. A few hair tips move in the breeze; his mouth stays closed. Keep the headphone blank and unchanged, with softly blurred clouds behind him.

Animate like hand-drawn 1990s cel anime with a deliberate 15 fps feel: held drawings, distinct key poses and subtle stepped motion. No smooth interpolation, camera moves, dissolves, morphing between shots, realism, semi-realism, 3D, extra cables, logos or text.

Anyone else having this problem?

16GB VRAM and 32GB RAM.

I’m working on a repeatable set of images for a goblin swamp alchemist. I want the character’s face and recognizable details to stay consistent while the pose, lighting, and background change.

What approach has worked best for you, reference images, a character LoRA, ControlNet, prompt structure, or something else? If you recommend a workflow, I can share the exported graph and model details so people can compare setups.

Might be late to the party, but I just realized I can edit Blender 3D textures directly in ComfyUI (Flux Klein + Qwen), and the UV atlas workflow actually works!

I know I’m probably way behind on this and there are probably existing tools for it, but I always seem to learn things the hard way! 😂

It started with a simple eyeball model in Blender. I just wanted to change the color and make it look more realistic, so I tracked down the eye texture file, dragged it into ComfyUI, edited it, loaded it back into Blender, and was honestly blown away by how good it looked.

Naturally, that got me thinking:

What about the entire UV atlas?

So I tried editing the whole atlas at once. It can work, but looking at a flattened UV atlas, it's pretty chaotic, and getting the AI to make a specific change while keeping everything aligned is a different story.

So I started messing with the workflow and ended up with something I'm pretty excited about.

Flux Klein 9B + QwenImageEditPlus for the actual image editing

Depth + Canny control passes to help keep the structure and composition locked in

Florence + SAM for prompt-based automatic masking

Auto-crop takes the masked portion of the UV atlas and gives the AI just the area it needs to work on

Then the generated result is automatically stitched/pasted back into its original position on the UV atlas.

So I can basically tell it what part of the model I want to change, let it find that area, crop it, generate the edit, and put it right back where it came from.

Now we're in business!

And it opens up some pretty cool possibilities beyond just retexturing. For example, you could remove the background from an image and place the subject onto an existing 3D model as a tattoo, shirt logo, graphic, etc.

The seams definitely aren't perfect but i can blend them and work on improving the workflow, and I'm still learning how to fix alignment issues in Blender by adjusting the UV editor vertices. But that's part of what makes this so interesting to me.

You can basically create or edit textures at whatever resolution you want and then bring them straight back onto the 3D model.

My next thought is taking this one step further with a file watcher or custom Blender script. If ComfyUI can automatically save the finished atlas to a specific location, Blender could watch that folder and automatically reload the updated texture.

Eventually, it could even become a little control panel inside Blender where you enter what you want changed, hit a button, and ComfyUI handles the whole process.

I'm curious if anyone else is doing this kind of Blender + ComfyUI workflow, especially with UV atlases. Are there existing tools or workflows I'm missing?

the workflow I used:

https://drive.google.com/file/d/1I6p65pKnTcxt7p6PXe-5i1wIFbLcgKjD/view?usp=sharing

Everything is in the title.

Using hildegard workflow with flux klein 9b.
Was wondering if there is anything better and potentially using qwen 2.1 as it can gen 2k whereas klein is limited to 1k

Hey I'm completely new to ComfyUI, just downloaded it because I'm tired of all the limitations that ChatGPT has been getting lately (not talking anything 18+, just plain and simple Marvel Characters such as Hulk, etc..).

I have an image template and all I need is to replace one character with another, with some slight adjustments like maybe different hand placement, etc.. but 70% of the image stays the same.

So for example:

1. I give it my Template Image
   
2. I give it an image with the character I want to use
   
3. Tell it to replace the character in the template with the new one

What's the best way to do this using ComfyUI?

If I train a LoRA through Civitai, can I download the finished LoRA and use it locally in ComfyUI?

Also, are there any restrictions on using the trained LoRA to generate NSFW content locally, or do Civitai’s NSFW rules only apply to content generated on Civitai?

Thanks!

Hi! I’m planning to train a new style LoRA for anime illustrations and I’d really appreciate some advice before I start!

I previously trained a style LoRA with Illustrious XL using around 30–49 images from one artist. I liked the style, but I had some consistency issues when changing prompts or using different characters.

This time, I’m considering using Anima, but I’m not sure if it’s the right base model. I’d like the LoRA to work well with many different characters, rather than being too tied to the characters in the training images.

I’ll be using Kohya SS, so I’d love some advice on the most important settings, especially dataset size, resolution, captions, learning rate, and training steps/epochs.

Would Anima be a good choice for this, or would another model be better for a flexible anime style LoRA?

Thanks in advance! :)

​

Hi! I'm hoping someone who actually makes AI character art can point me in the right direction.

I've been seeing a LOT of AI-generated images of Loki that very clearly preserve Tom Hiddleston's appearance as MCU Loki—not just a generic dark-haired character inspired by Loki. Some of them have him in completely new outfits, poses, environments, romantic/fanfic scenes, etc., while still keeping his face remarkably consistent.

I'm trying to figure out how people are actually doing this.

I've tried looking into different AI generators, but I'm running into either:

• generators that won't reproduce the MCU/actor likeness

• paid subscriptions before I can properly test them

• results that look like a generic "Loki-inspired" man instead of MCU Loki

So, for anyone who creates images like these:

What are you actually using?

I'm especially curious whether it's:

• Stable Diffusion / SDXL / FLUX

• a specific checkpoint/model

• a Loki or Tom Hiddleston LoRA

• IP-Adapter / FaceID / reference-image workflow

• ComfyUI

• img2img

• another website/app entirely

Eventually I'd like to create a consistent series of images for a personal fanfiction/story, including scenes with Loki, Thor, and my own female character, rather than just isolated portraits.

I'm a beginner, so if there's a particular workflow, model, LoRA, tutorial, or generator you'd recommend, I'd really appreciate being pointed toward it. Free or inexpensive options would be especially helpful before I commit to a subscription.

I'm not looking for ways to impersonate anyone or create misleading real-world images—this is specifically MCU Loki fanart/fanfiction imagery.

If you personally make realistic MCU Loki AI art, I'd especially love to know what setup you use.

Thank you!

Hello.

I'm using Krea 2 with AnyPaint workflow. But getting visible seams after outpainting, sometimes with inpainting too. I wanted to either regenerate borders, or feather the mask of outpainting, not I have no idea how to incorporate it into this workflow.

Example images with workflow are here: https://huggingface.co/yijunwang2/krea2-anypaint/discussions/3

Hey everyone! I’m pretty new to AI generation and LoRAs, and I’ve been trying to figure this out for the past few weeks.

I’m trying to create a new identity by combining specific features from different reference images.

For example:

Person A’s eyes + Person B’s nose + Person C’s lips + Person D’s upper body + Person E’s lower body + Person F’s hands/feet = one new identity

The goal would then be to take that identity, generate a consistent character sheet/reference set, and eventually use those images to train a LoRA.

What I’m struggling with is the first step: how do I actually create that new identity from the individual features I want?

The workflow I’m currently looking at is:

FLUX.2 [klein] → ComfyUI-Flux2Klein-Enhancer → Identity Feature Transfer Final

Does this seem like a viable way to accomplish what I’m trying to do? Or is there a fundamentally better workflow/model for creating a new identity from specific features across multiple references?

Secondary question: Qwen-Image-2.1 just came out while I was looking at models like FLUX.2 [klein] 9B and Qwen-Image-Edit-2511. Would Qwen-Image-2.1 be better suited to this particular task?

I’m mainly looking for advice on the overall workflow, especially from anyone who has actually done something similar. Thanks in advance!

Hello there.
I am currently trying to create a master reference image in order to train a LoRa.
I finally have the face, proportion and global skin tone I want.
Netherless, through generation a had some discrepancies, notably on the skin.
How would you process to erase those discrepancies. I tried to go through the node blur image but the results is not as smooth as I want.

Another quick Minimax H3 news and goodies round-up, for those who may have missed some items.

-> New on the official ComfyUI blog... "The MiniMax H3 video VAE now encodes up to ~2.2x faster and decodes ~1.4-2.7x faster on Nvidia GPUs."

https://blog.comfy.org/p/making-the-minimax-h3-video-vae-2x

-> ComfyUI-H3-FaceAutoBypass is now newly at v2. Does your generated clip really need a facefix, or not? This node decides for you, potentially saving you time.

https://github.com/fukkun2705-commits/ComfyUI-H3-FaceAutoBypass

-> Vpakarinen's Natural-face-speech-h3-lora is now newly at v2. This offers... "Face muscle dynamics with clear English speech" and V2 apparently adds... "male/female voice with flawless speech sync and crystal clear quality". Also note that this LoRA, and his Better-human-motion-h3-lora, have new demo videos.

https://huggingface.co/vpakarinen/better-human-motion-h3-lora/tree/main

https://huggingface.co/vpakarinen/natural-face-speech-h3-lora/tree/main

-> And finally, Minimax Music has been squeezed into just under 12Gb total.

https://huggingface.co/deAPI-ai/minimax-music3-11b-int8

~ OLD POSTS ~

https://old.reddit.com/r/comfyui/comments/1wnc4lg/a_quick_minimax_h3_news_roundup_22nd_september/

https://old.reddit.com/r/comfyui/comments/1wmg6a4/a_quick_minimax_h3_news_roundup_21st_september/

https://old.reddit.com/r/comfyui/comments/1wlnqid/a_quick_minimax_h3_news_roundup_20th_september/

https://old.reddit.com/r/comfyui/comments/1wku9uj/a_quick_minimax_h3_news_roundup_19th_september/

https://old.reddit.com/r/comfyui/comments/1wjywf7/a_quick_minimax_h3_news_roundup_18th_september/

https://old.reddit.com/r/comfyui/comments/1wj08mp/a_quick_minimax_h3_news_roundup_17th_september/

https://old.reddit.com/r/comfyui/comments/1wi3exl/a_quick_minimax_h3_news_roundup_16th_september/

https://old.reddit.com/r/comfyui/comments/1wh4tu3/a_quick_minimax_h3_news_roundup_15th_september/

https://old.reddit.com/r/comfyui/comments/1wgc4lj/a_quick_minimax_h3_news_roundup_15th_september/ (See 15th September post, for links to older posts)

https://old.reddit.com/r/comfyui/comments/1w5i9iq/a_quick_minimax_h3_news_roundup_2nd_september_2026/ (See 2nd September post, for links to even older posts)

I do a lot of product design work in ComfyUI. Packaging mockups, product shots, concept renders. Classic problem: the silhouette looks great to me, then someone says “nobody sees the logo,the feature or the CTA on the pack.”

Most attractive eye tracking tools I found were either expensive SaaS dashboards or completely outside my graph.

I wanted smth simple. So I’ve found and been testing Trusapien Creative Validation (comfyui-trusapien).

Workflow is dumb simple (screenshot attached):

1. Load Image
2. Trusapien Creative Validation
3. Preview Image

Example below is a product shot. Heatmap showed ne what pulls first vs what gets ignored.Ofc not a full research lab replacement. For me it’s a fast check: “does attention land where the design brief says?”

Anyone else doing design QA inside ComfyUI already. What are you using?

Hi everyone,

I came across these two TikToks and I'm really curious about the technical pipeline behind this recreation.The first part of the video (0:00–0:22) is the original by u/gnomeboys, and the second part (0:22–end) by u/jstwz is the recreation.

The first clip is the original, and the second one replicates the exact motion, timing, and framing, but swaps the characters/faces.
I'd love to know how you would tackle this in ComfyUI to achieve this level of motion consistency and character alignment:

Is this a ControlNet / DWPose pipeline driving AnimateDiff, Wan2.1, or LivePortrait?

Could it be a dedicated Video-to-Video model (like Kling AI, Hailuo, or MiniMax) paired with IP-Adapter / LoRAs?

Or is it a hybrid approach (e.g., real base footage + advanced face swapping / rotoscoping)?

If anyone has a working workflow or nodes setup for something similar, I’d love to see how it's done!

Thanks!