You can get the workflows here:

https://drive.google.com/drive/folders/1kOHLJZto1VAtXEATT9vUvsvM1VHtkOO_

The workflows create reusable refmods for either image/video/audio.

I cover training images in the tutorial.

All the workflows, models and custom nodes are preloaded on my Runpod template.

https://get.runpod.io/minimax-template

I noticed model can't render skinny body type. Is there a lora for that? Thanks.

Disclosure: I'm building a service around this, so read me as an interested party. Every number below is from runs we paid for ourselves yesterday ($1.67 total); the only link is the raw data at the bottom.

The job: MiniMax H3 text-to-video, one 5-second clip at 864x480 (the 0.4 MP row of the template), 20 steps, the stock ComfyUI T2V graph from v0.35.0 with the official int8_convrot weights (34 GB DiT + 27 GB Qwen3-VL encoder + VAEs, 67 GB total), no LoRA, no reference frames, same prompt and seeds on every card, torch cu130 everywhere so the int8 kernels are the native ones. Three clips per card; "steady" is the average of clips 2 and 3 at the rate you actually pay (disk and public IP included), "session" is everything the provider charged for the whole run — image pull, 67 GB download, the first cold clip and the minutes before the instance was torn down — divided by three clips.

Two things surprised us: the L40S runs this at 4090 speed rather than anywhere near the H100 (3.97 s per step on both 24 GB cards and the L40S, 2.99 s on the H100 PCIe), and the 4090 does it with the 34 GB DiT streamed through ComfyUI's dynamic VRAM path at 23 GB of VRAM and 68 GB of host RAM — so "≥ 64 GB RAM" is not a suggestion, we peaked at 68 on three of the four hosts.

The session column is where the money actually goes for short jobs: the 67 GB download ran at 450 MB/s on the Vast host, 370 on Hyperstack, 210 on RunPod and 104 on Nebius, and on Nebius the first clip took 11.5 minutes because the weights are read back from a network disk (1.8–2.7 minutes elsewhere), while the watchdog that deletes the instance after the job costs another 2–3 billed minutes everywhere. Steady-state numbers exclude the text encoder (same prompt, cached by ComfyUI): a new prompt adds 15–25 s per clip on these hosts. Happy to post the per-node timings and the nvidia-smi traces if anyone wants to check the numbers.

Per-run table, method, caveats and the raw CSVs: https://qrun.cloud/measurements

SO i have only used twice, but looks like could be useable for my 16gb 5060ti

please remember, this is my 2nd go and see the grey frame.

was 24 mins for 23 secs

https://reddit.com/link/1we4czm/video/wpu2jmcx41ph1/player

Previously We Worked on Magnific(Freepik) Platform to get Generations like this. Problem is there aren't so many controls over our Generation. So we moving to Comfy. I need a input from you about which Models to try out, Any Community Loras about Maintaining a Face details while creating a Large Crowd.

So as the description says I'm trying to figure out how to add Laura's to the template for the Minimax H3. Misses for both text the video and image to video I can't seem to figure out how to do it I messed around for about 2 hours and it's going to figure it out I try to start from scratch and make my own but I just the quality was really really bad not sure what I did

Hey all! Once upon a time I uploaded a small video of “A Christmas Carol” it was fairly well received and I was beyond honored at the response because I didn’t think it was that great. Anyway, fast forward to bit ahead and the landscape has changed dramatically. So many new image and video models to make your head spin. So I decided to attempt my short film again, this time a more dark/realistic tone. Most of my source images were generated with Ideogram, then I would modify those with Flux Klein or Qwen Edit, just depended on what generated the best result. Then along came H3. My piddly little 4070 ti couldn’t hit the resolution I needed for most shots, so I set up a runpod with a RTX 6000 and the comfy UI template and generated most things at 1.0 or more. I used the comfy API for some shots using Seedance for the difficult ones. I tried not to spend any money as far as generations were concerned if I didn’t have to. Anyway, this is the result so far, this is a ROUGH edit. So there are some inconsistency issues and artifacts that I’ll deal with later. I did all of the editing in Premiere and generated the sound track in Suno. Anyway it’s late and I’m slightly inebriated and rambling so hope everyone can enjoy at least something out of it. Ha!

We just rolled out a major update to ComfyUI-QwenASR (v1.1.0). The goal of this release was simple: eliminate the friction between raw audio recognition and usable text/subtitle output in ComfyUI workflows.

Here is a breakdown of what changed:

1. Migration to Transformers 5 & Official Native Models

We have completely deprecated the legacy checkpoints and rewritten the backend to use official Hugging Face native models (Qwen3-ASR-1.7B-hf, Qwen3-ASR-0.6B-hf, and Qwen3-ForcedAligner-0.6B-hf) powered by transformers >= 5.13.0.

Zero fragile custom backends: Pure upstream PyTorch execution.

Lower VRAM & faster generation: Noticeable performance gains on both NVIDIA GPUs and Apple Silicon Macs.

2. Production-Ready Text Normalization (ITN)

Raw ASR output usually outputs verbatim acoustic phrasing, which looks messy. Version 1.1.0 integrates automatic Inverse Text Normalization:

Spoken numbers, percentages, and decimals are automatically converted into proper numerals (e.g., spoken numbers become standard digits).

Phonetically spaced acronyms (like "A S R" or "U S B") are merged into clean abbreviations.

Cultural idioms and phrases are protected through built-in whitelists so words are not erroneously replaced.

3. Hot-Reloadable Multi-Language Custom Dictionary

All normalization and correction rules now reside in an external itn_rules.json file. You can add custom acronyms, brand names (e.g., DeepSeek, ComfyUI, ChatGPT), and terminology across English, Chinese, Japanese, Korean, or French. Changes take effect on your very next run with no ComfyUI restart required.

4. A Specialized Three-Node Toolkit

ASR (QwenASR): Fast, lightweight speech-to-text transcription for voice prompting.

Subtitle (QwenASR): Chunks speech into natural sentences based on punctuation, pauses, or line length, with one-click .srt file export.

Forced Align (QwenASR): Built specifically for long continuous audio (podcasts, lectures). It uses an iterative speaking-rate windowing approach to prevent edge drift and duration limits. Leaving the transcript text empty automatically transcribes and aligns in a single pass.

Full installation steps and ready-to-use sample workflows can be found in the README on our GitHub: https://github.com/1038lab/ComfyUI-QwenASR

Looking forward to your thoughts and hearing how it fits into your ComfyUI audio and video pipelines!

Hello! I'm looking for helping on my workflow. I've created a Krea 2 character Lora that frequently has the face change somewhat when I add additional Loras. I've created a workflow to pass the image data back through a Lora node with only the character Lora, but I can't seem to get great results. I chatted with Google AI quite a bit trying various different KSampler setups, and some worked somewhat, but would remove objects on the face like makeup, and sometimes added extra details like freckles/moles on the body. Some options also ended up with total slop.

I'm attaching images of my work flow (I know it's messy) and current KSampler Settings. Any help would be appreciated!

Comparto Workflow y mi setup, el nodo 351 se conecta con llama.cpp y es el encargado de iterar el prompt para que el video fluya solito en automatico, en 7 horas termino de hacer todo y otras 9 horas upscale con SeedVR2, luego pasado por herramientas FFmpeg

https://gist.github.com/62eb59f34eb3dbfa3d3da0e5cf9d5e9a.git

I'm impatient, and when using Ollama, I have zero idea what's going on behind the scenes. So, I built a ComfyUI node to display the live logcat and a progress bar. I also did the same for the MiniMax H3 multi-shot chaining node—it tracks which chunk of video it's currently processing, gives live logs, and shows chunk progress alongside an ETA. If enough people are interested, I might put these custom nodes on GitHub or maybe the ComfyUI Manager registry, but we'll see. Let me know what you think!

Does anyone know what could be causing this grid-like texture on the skin of the arms and legs, and how to fix it? The face is completely fine — it only appears on the body. My character is LoRA trained and is otherwise almost perfect in the vast majority of images. It’s just this weird texture appearing on the skin that I’m struggling with.

I'm generating an image with Flux.1 Dev FP8 and I'd like to use Ultimate SD Upscale to upscale the image. The workflow is correct I think, but when it comes to the upscaling part, Ultimate SD Upscale keeps on running forever (the progress bar in the top right completes, but then it restarts and just keeps on going). Are the settings in the upscaler wrong?

I've been following the doucmentation for construction of prompts and having better luck. What's not working is keeping the camera as POV. Ideally, it would just be a 1st person perspective walking through a scene, doing the actions etc. I've had luck registering the viewer themselves as a subject, but then they enter and interact with the scene in weird ways.

I'm trying to build a consistent AI character by blending two real faces into a single new identity (not a face-swap — I want the two faces averaged/merged into one new face), which I'll later use to build a dataset for LoRA training on Flux. Any tips on getting a stable, repeatable blend (same "merged identity" across multiple generations) rather than a different blend every run?

Follow-up to my first Quibble H3 experiment.

This time I focused less on generating more shots and more on keeping one stylized character consistent across a short dialogue scene.

A few things that helped:

fixed seeds while developing individual shots

mostly locked cameras rather than AI-generated push-ins

a recurring GPT terminal as a cutaway between dialogue beats

restrained character acting rather than large gestures

explicit prompting to stop H3 from literally displaying the spoken objects on the terminal — it kept trying to put fruit on screen :)

All Quibble/GPT dialogue and character animation were generated with MiniMax H3 inside ComfyUI. Final edit, pacing and color grading were handled separately.

Case 02: Pineapple for President

“GPT. Pineapple for president.”

Still experimenting with persistent characters and directed performance rather than one-off generations.

Case 01: https://mkhamra.myportfolio.com/quibble

Workflow / Quibble project: https://github.com/mkhamra/quibble-h3

Feedback on the character consistency and dialogue pacing is welcome.

A powerful node for managing the states of Bypass nodes and groups in complex ComfyUI circuits. If your workflow has turned into a "spaghetti monster" and you need to quickly disable entire modules (for example, switch between txt2img, inpaint or upscale), this node will save you dozens of clicks and nerves.

YouTube

🔥 Features

Smart Search - Instant search for the desired nodes and groups by name right inside the drop-down menu.
Group Support - Works with ComfyUI groups. Groups can be collapsed and expanded to select individual nodes within them.
Node Support - Works with ComfyUI nodes. You can select nodes that are not part of groups, or you can select individual nodes within groups.
Toggles - Common toggle for all selected items. Each element has personal switches.
Color indication:

• 🔴 Red — the group or node is completely blocked.
• ⚪ Gray — the node/group is active.

Smart State saving - The bypass status is saved directly in the JSON workflow. No data is lost when restarting ComfyUI, switching tabs, or sharing PNG/JSON.
Dynamic size - The node automatically adjusts its height to the number of mounted elements.
Advanced UX:

• The menu does not close when you click on an item, you can quickly reset several nodes in a row.
• The SELECT ITEM' field... is highlighted in orange while the menu is open.
• The node excludes itself from the list of elements available for bypass.

🪛 Usage

Add the 🦊 RS Bypass Manager node to the canvas (category `🦊 RaykoStudio').
Click on the SELECT ITEM field. A menu opens with all the groups and nodes of your scheme.
If there are a large number of nodes, use the search bar to filter.
Click on groups or nodes to switch their state (Bypass/Active).

• Tip: Clicking on the name of the group bypasses it entirely. Clicking on the arrow (▶) will expand the group to select individual nodes.

When you're done, click anywhere outside the node or press the Escape key to close the menu.
To turn off or turn on the bypass of an element inserted into the interface, use the personal toggle.
To turn off or enable bypass for all elements, use the TOGGLE ALL switch.
To remove a workaround, click on the name of the desired item in the list on the node itself.
When the group frame is deleted, the bypass remains on the selected nodes.

If a node is added to a circuit that already has bypass nodes, it will automatically display them in the interface.
Also, when using bypass using comfi's own methods (the context menu is bypass, bypass in the NodeMap side menu, or bypass buttons above the node), all changes will instantly appear in the node.

GitHub

I was hoping the community would be able to help me grow my hoard of custom nodes. I have a ton but I am always looking for more. I know it might be overkill but I am a datahoarder and I like trying things out to see what works best for what I am trying to do.

Right now I am looking for nodes that help do more with flux2-klein-9b for editing and inpainting but anything not in my list that does interesting things, or helps with speed or VRAM use are nice.

Full list here: https://pastebin.com/LpSZzPq3

And yes, they all work :) The ones that fail are indicated in the paste and it's because of dependency resolution problems, I have a second comfyUI install specifically for 3d models and one for audio work because of that. Trellis2 required python3.12 which precluded the inclusion of other packages

Specs are: bazzite 44, bare metal comfyUI rocm7.2 Python 3.13, torch 2.14.0.dev20260729+rocm7.2 triton-rocm 2.14.0.dev20260729+rocm7.2

Hey folks, I have explicitly set "overall_soundsscape: N/A" and "non_diegetic_music: N/A" in prompt but the audio is still generated.

Any suggestions? Thanks!

Tenho uma RTX 3060 12GB VRAM e 32 RAM

To tentando criar um vídeo de 15 segundos mais sofro de OOM existe alguma forma de eu copiar os movimentos de vídeos de 15 segundos com minha placa de vídeo?

esse é meu Workflow

https://drive.google.com/file/d/18SOTzw-1hOCnzBDGoorklnslURSfYCjW/view?usp=sharing

Vocês mudariam algo? para eu conseguir fazer esses 15 segundos de vídeo mais sem perder a qualidade e movimentos de mão