Mine always start organized and somehow end up looking like this. Any tips for keeping bigger workflows clean and actually readable without spending forever rearranging nodes?

So basically, I saw a workflow on ComfyUI’s official LinkedIn where they used a model image, a product image, and a background image with Google and Kling APIs to generate a one-shot ad using a single camera angle.

So I challenged myself to recreate the idea using only local open-weight/open-source models, but make it more ambitious: multiple shots, multiple cuts, and everything directed through a single prompt.

And it worked.

For this, I used the basic MiniMax H3 Reference-to-Video workflow in ComfyUI:

https://docs.comfy.org/tutorials/video/minimax/minimax-h3#minimax-h3-reference-to-video-r2v

Then I used ChatGPT to help structure the video prompt. I provided the reference images and gave it this direction:

“Write a MiniMax H3 reference-to-video generation prompt to create an ad. Add sound FX and music prompts as well.

Shot 1: Medium close-up. She is about to open the can.
Shot 2: Extreme close-up of the can as she opens it. Can-opening sound FX.
Shot 3: Close-up as she drinks from the can. Gulping soda sound FX.
Shot 4: Close-up as she holds the can forward and smiles.”

The final result was generated locally on my RTX 5070 Ti using ComfyUI.

Hey everyone,

If you’ve spent any time working with multi-reference video prompting in ComfyUI (especially with MiniMax Hailuo / H3), you probably know the frustration:

You feed in 3–4 reference images hoping for a cohesive 15-second cinematic shot, and the LLM spits out a rushed single-shot prompt where characters overlap chaotically, faces get stretched, pacing flickers, and dialogue cuts off halfway through.

Our team at 1038lab just pushed a massive overhaul to ComfyUI-MiniMax-H3-Promptor (v1.3.0). We threw out the old "single-shot rush" approach and re-engineered the prompt pipeline to work like an actual film production crew.

Here is what we added in v1.3.0:

1. Two-Stage Hollywood AI Director & Screenwriter

Instead of rushing the final prompt in one go, the node now executes in two deliberate stages:

• Stage 1 (Director Blueprint & Global Vibe): The LLM acts as the showrunner. It analyzes all your cast references, maps out spatial layers (Foreground, Midground, Background), sets lighting palettes, and calculates shot pacing (enforcing a 2.5s–4.0s minimum per shot to prevent pacing flicker).
• Stage 2 (Storyboard & Dialogue): Using that approved blueprint, it crafts timed cuts covering the full duration (up to 15.0s) and injects official MiniMax character dialogue syntax (<Subject 1> (S1) [angry] says: <d>[EN] "..."</d>).

If you pass in a custom scene prompt, the engine treats it as the supreme mandate, directing your uploaded cast and props to execute your exact vision.

2. In-Node HTML Drop-Zone (No More Noodle Spaghetti)

Wiring up 5+ image loader nodes for multi-character setups makes workflows messy fast. We replaced the PyTorch image input slots with an interactive in-node HTML/JS drag-and-drop panel. You can drop images, video references, and audio files straight onto the node canvas.

3. Vision Analyzer V2: Native Aspect Ratios & 50% Lower Token Cost

• Zero-Deformation List Expansion (OUTPUT_IS_LIST): Passes references in their 100% original dimensions through native list iteration. No forced letterboxing, cropping, or distorted face proportions.
• Pure Perception Engine: We stripped out redundant text synthesis so the VLM only extracts raw visual traits (clothing, colors, contours, OCR). This cut API token usage and latency roughly in half.

4. Quality-of-Life & Stability Upgrades

• Smarter Entity Regex: Fixed false positives so items like a "cat-ear headband" are recognized as accessories on a person rather than spawning wild animals into your scene.
• Sub-Batch Chunking: Set custom Max Batch Images limits with positional fallback keys to respect upstream API rate limits without workflow crashes.
• Real-Time Terminal Execution Trace: Clean phase banners in the ComfyUI terminal let you monitor the Blueprint -> Storyboard -> Assembly stages live.

💡 A Note on APIs: 100% Free & Local-Friendly (No Paid API Required!)

We’ve noticed some users hesitate whenever they hear "LLM/VLM API," assuming it requires paid subscriptions or goes against the open-source ethos. That is not the case here!

Our node is fully customizable and seamlessly supports:

• 100% Free Local Models: Plug directly into Ollama, LM Studio, or llama.cpp to run any open-source model from Hugging Face locally on your own GPU.
• Free Cloud Tiers: If you don't want to run local LLMs, services like OpenRouter, Groq, and NVIDIA NIM offer generous free tiers/credits that are more than enough for daily video prompting.

Setup takes just a few clicks—use whatever setup works best for your hardware and budget.

Links & Getting Started

• 📦 GitHub Repository: https://github.com/1038lab/ComfyUI-MiniMax-H3-Promptor
• 📝 Full v1.3.0 Changelog: https://github.com/1038lab/ComfyUI-MiniMax-H3-Promptor/blob/main/updates.md#v130-20260818

You can update directly inside ComfyUI Manager or run a git pull in your custom nodes directory.

We’d love to hear your thoughts, bug reports, and workflow suggestions!

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

-> New in version 4.1.2 (19th August 2026) of the Fizgig trainer for LoRAs... "Minimax H3 now trains on video clips, on their sound, and on voice recordings alone: photos, clips and voice files in one folder to train one LoRA in one run". Fizgig can do so locally in 16Gb VRAM, without slowdowns. Adds a fix so the LoRAs will work correctly on both the 4-step Turbo or the official workflow, and has also benefitted from a major security audit. Fellow-Brit and industry professional Shoot The Sound has a good 20-minute tutorial today on YouTube, using the latest Fizgig and its dataset prep tool, to train a character+voice LoRA.

https://github.com/shootthesound/Fizgig

https://www.youtube.com/watch?v=lVqSgsPpF0c (Fizgig 4.x tutorial)

-> ComfyUI-MiniMaxH3-SingleFrame. Two still-image generation nodes, with the second being especially interesting. Given the usual first/last frames, it attempts to interpolate/generate a plausible single 'middle frame'. Has workflows, and requires no ComfyUI Core patching or special VAE.

https://github.com/tori29umai0123/ComfyUI-MiniMaxH3-SingleFrame#english (English ReadMe section)

-> A new H3 Prompt Journal. Some scenes require complex physical logic from the camera. The Journal's first three entries demonstrate how to write prompts for such scenes: for a 'Three-Person Occlusion-Linked Orbital Long Take' (e.g. elegantly redirect the camera between three moving people, in a single take); 'Dual-subject-speed-contrast' (e.g. a dancing master leads in a waltz, while his hesitant student follows his moves); and 'Single-subject-three-pose' (e.g. input three poses for one character, then have a gnat-sized camera... "sweep past feet, legs, torso, shoulders, hair - constantly redirecting around the moving [giant] body without ever slowing down").

https://github.com/LoveRain1997/h3-prompt-journal

-> 'Video -> H3 Prompt'. An "end-to-end pipeline that turns a video file into a ready-to-paste MiniMax H3 generation prompt". Appears to be a 'skill' for use with a local installation of OpenAI's Codex, which is a lightweight coding agent.

https://github.com/LoveRain1997/video-to-h3-prompt

https://github.com/openai/codex

-> For MiniMax Music, a new rvq-encoder-169m-v4.onnx (676Mb), an... "encoder that turns audio into the codes Minimax generates, so a finished track can be handed back" to Minimax Music for further work. With this Minimax Music can continue a track. Or the user can replace a section, or even re-generate the same song but with a different performance. The ONNX format is very portable, and I guess it's only a matter of time before a ComfyUI workflow appears.

https://huggingface.co/nerualdreming/open-rvq-encoder-minimax-music3-169m-v4-onnx

-> And finally, a detailed benchmarking of "the official reference-to-video workflow" on an RTX 3060 12Gb. Most low-VRAM users will of course be running smaller Minimax models in a 3060-optimised workflow. But... there's still important advice here for those considering buying a second 3060. They say... "Two cards are still not one big card. Two RTX 3060s do not present 24GB to a workflow, and our attempt to at least run two jobs in parallel was blocked by system memory rather than VRAM."

https://www.minimaxh3tutorial.com/rtx-3060

I made Window Assassin, a tiny Windows tray utility for those moments when an app freezes and refuses to close.

Focus the window and press Ctrl+Alt+End. It immediately terminates the process behind the active window.

Features:

• global Ctrl+Alt+End hotkey

• elevated execution for stubborn apps

• optional Start with Windows

• installer and portable ZIP

Warning: forced termination skips save prompts, so unsaved work will be lost.

Free / pay what you want: https://b2kdaman.itch.io/window-assassin

recently made a 90-second AI short film called “The Fence.”

the whole thing is made up of 6 shots, each 15 seconds long, and it took me around 3 hours from generation to the finished video.

the main thing I wanted to test was how far a mostly local AI workflow can currently compress the process of making a short film.

The workflow was basically:

idea → images → 6 × 15s video clips → voice/audio → edit → 90s film

The interesting part is that generating wasn't really the most time-consuming step. most of the work went into figuring out what each 15-second section actually needed to show.

I first broke the 90-second story into six relatively self-contained shots. Then I created key visuals for each one with Qwen Image 3 Pro before sending them into MiniMax H3 for motion.

I found this much easier to control than trying to generate the whole thing directly from text. It also means that when one shot fails, I only need to redo those 15 seconds instead of rebuilding the entire sequence.

what surprised me most was the speed: roughly 3 hours for a 90-second finished experiment. obviously this still isn't traditional filmmaking, and there are plenty of typical AI-video issues around motion, character consistency, and continuity between shots.

but for a one-person experiment, the production speed is kind of wild.

I'm starting to feel that making AI films is becoming less about finding one “perfect” model and more about building a workflow where different models each handle the part they're good at.

Two weeks ago I posted here about Stimma, the open-source desktop app I've been building on top of ComfyUI. It's been a really fun couple of weeks talking with many of you and working through issues and improvements that came up in those conversations. Since then, I've made a couple of releases, but this one is particularly relevant to ComfyUI, so I wanted to share it here.

One of the main themes in the early feedback was a fear of getting things set up with ComfyUI. Some people who had already churned out of ComfyUI's onboarding were wondering if Stimma could make it easier. Some were just anxious (understandably) because setting up anything new with ComfyUI can take an evening. Others tried and ran into some head-bumps.

I said in that post that I don't want Stimma to manage a private ComfyUI install for you, and I still believe that. There are too many variations in how people deploy ComfyUI in the real world, and every product that I've seen that installs ComfyUI for you ends up limited.

From Stimma 1.0.13, the only things you should need to do on the ComfyUI side are: run ComfyUI and add the ComfyUI-Stimma custom node. After that, it should be possible to manage ComfyUI from within Stimma.

I'm sure people will run into some rough edges with this over the next few weeks, but I've done a lot of fully clean ComfyUI+Stimma installs over the past few days on various platforms and systems and it's working well enough that I'd like to start the feedback train rolling. If you do run into trouble, please get in touch here or in the discord.

The video above shows a fully local setup of Stimma. ComfyUI and vLLM are running on a DGX Spark to provide AI capabilities. The video starts from a fresh ComfyUI + Stimma install, and ends with generating an image. I ran Stimma on my mac because I have better screen recording software there, but you can actually run this full stack on the GB10 box locally.

Once you're running Stimma and ComfyUI together, there is a new button in the app bar that opens a manager. This includes:

• Every workflow that ComfyUI-Stimma discovered. For workflows missing dependencies click "Get Ready" and it will coordinate downloading models and installing custom nodes.
• GPU utilization + VRAM information
• A list of running jobs with cancellation
• The ability to update ComfyUI-Stimma from within Stimma, restart ComfyUI remotely, etc.

Some other things that landed in 1.0.12 / 1.0.13:

• Works without a chat model. Some people want to use Stimma without devoting VRAM to an LLM. This was always possible, but wasn't a very smooth experience. That is fixed, and Stimma should now degrade gracefully when no Chat Models are configured.
• Live previews during image and video generation. This is disabled by default, but you can turn it on in settings->preferences. Please let me know what you think.
• LTX-2.5 support in ComfyUI-Stimma: text-to-video with audio, image-to-video with optional end frame, extend, loop, stitch, up to 10 LoRAs.
• Anima and H3 LoRA support in ComfyUI-Stimma
• Fixes for extra_model_paths.yaml, nested model folders, top-level reroute nodes, Windows FFmpeg detection, and source-folder / slideshow / editor bugs.
• Performance Optimization throughout the image editor, and a new patch tool implementation that blends better.
• Ask Stimma: the chat agent can read Stimma's docs now and help walk you through setup and product questions.

One thing from that thread I haven't gotten to yet is the Draw Things backend. I am reaallly hoping that the Draw Things team pays some attention to this bug because fixing this is the best path that I can see to a good experience using the products together. If you're on github, please go to that thread and make some noise, maybe they will pay attention.

I hope this ComfyUI manager stuff encourages a few more of you to give Stimma a shot. If setup continues to be a pain, I'll keep at it.

To get the new stuff, you'll want to update ComfyUI-Stimma and also and update Stimma itself in-app or with a git pull if you're running from source.

As always, please reach out on Reddit or Discord with any questions, feedback, or issues. It's been a lot of fun talking with everyone.

Links: Download · GitHub · ComfyUI-Stimma · Docs · Discord · /r/stimma

Custom node v0.2.0 is out and U1.5 works in ComfyUI now.

What it does: text-to-image, image editing (single and multi-image reference), and region-controlled edits via masks / bboxes / visual markers. Native 4K. It's a unified model, so understanding and generation share one backbone — no separate VAE, no CLIP/T5 text encoder in the graph.

VRAM: peak allocated is 17.34 GiB for T2I and 20.00 GiB for editing, using the offload modes. So a 24GB card handles both. There are full / fast / balanced / low modes to trade speed for footprint — balanced and low got 36–50% faster in the last release, and outputs are bit-identical across modes.

Repo: https://github.com/OpenSenseNova/SenseNova-U1

ComfyUI node: https://github.com/OpenSenseNova/SenseNova-U1/pull/244

Hi r/comfyui, Comfy MCP is now local and open-source!

When we shipped Cloud MCP in June, the response was immediate and consistent: make it work locally. So we did and it's fully open source.

Connect Claude, Codex, Cursor, or any MCP client to your local ComfyUI.

Your agent reads the GPU you actually have and gives you a straight answer on whether a model is worth running before you commit to the download. It reads every node and model you've installed. It handles the setup that usually stops people at step one.

It is now the easiest way to help with your local Minimax H3 workflows!

Cloud MCP still does everything it did. Tell your agent where a job goes, or let it decide.

MiniMax H3 is great, but it’s a total compute hog.

I tested two ways to speed it up—Turbo LoRA (reducing step counts) and Kitchen Attention (faster per-step backend)—using the exact same prompt, seed, and resolution.

Video review here

Edit: Here’s the workflow, if you want to test it out - https://drive.google.com/file/d/1425fNNR_C9ErIiutR_FBhtQlOKzJ_Tfh/view?usp=sharing

The Breakdown:

• Turbo LoRA: Cuts steps, but quality tanks. At 8 steps it gets soft and drifts; by 4 steps it's completely broken with heavy face artifacts.

• Kitchen Attention: Keeps all 20 steps, but chops ~30% off the render time with zero quality loss. Just update ComfyUI and set it in the attention backend node.

• LoRA + Kitchen Attention: The backend isn't causing the artifacts—the LoRA is.

audio stays decent at low steps even while the visuals fall apart.

Verdict: Skip the Turbo LoRA for now. Kitchen Attention is basically a free 30% speed boost, so just leave that on.

Look at your task manager while having your ComfyUI open, it has been eating 30% of my GPU due to preview nodes and what not. Minimizing it and then just occasionally opening it to check out the progress has sped things up by quite a margin. You folks probably already knew this, but I just wanted to share for everyone else that might be new to this like me.

An experimental temporal ghosting / long-exposure toolkit for TouchDesigner, built for turning prerecorded and real-time footage into smeared, split-exposure, echo-like motion.

The system layers delayed frames, masks the active subject region, and adds optional feedback persistence to generate distorted portrait, face, and full-body trails that sit somewhere between long exposure, temporal rupture, and spectral motion blur.

This release also includes:

— a custom FLUX-2 LoRA trained on experimental photography [the one used in this demonstration]
— the pertinent ComfyUI workflow for FLUX-2.dev + LoRA text-to-image generation

Available now through my Tools Store.

Both music and visuals by myself, deeply inspired by the recent BoC-related events.

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

-> New to me are the 'ComfyUI H3 Motion Context — MultiRef & Latent Masking' custom nodes for ComfyUI. (Hat-tip: I learned about it via the charming fellow-Brit Nerdy Rodent on YouTube). Lets you add keyframes at any point, not just first/last. Can also seamlessly extend an existing video, while taking measures to... "reduce RAM and cache pressure during long-form final output". Has workflows. Updated yesterday, with new features including the claimed ability to chain... "a sequence of H3 video clips around a single song".

https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef

-> Minimax Music has a new set of concept slider LoRAs. Including 'breathy vocals', and a 'live performance to a crowd'. With ComfyUI workflows.

https://huggingface.co/ntc-ai/minimax-music3-concept-sliders

-> New ComfyUI-CGlide custom nodes for Minimax in ComfyUI. Including 'Glide Preview', a motion-preview node that lets you assess your video as it generates. Only at seven frames per second, but it may give you the confidence to cancel the generation if things seem awry.

https://github.com/CGlide/ComfyUI-CGlide

-> ComfyUI-H3-Context-Noise. This tapers off the colour in the tail-frames of the previous shot, thus preventing colour residue from spoiling the seams between your shots. If you notice this problem, give it a shot.

https://github.com/beijinren/ComfyUI-H3-Context-Noise/blob/main/README.en.md (English version of the ReadMe)

-> A new archive of Minimax H3 style LoRAs. The most interesting being an comic-book style in the AstroWitch - Cinematic Comic Style - MinimaxH3 - ASTROWITCHV01H3.safetensors file, with ASTROWITCHV01H3 as the trigger-word. The first non-Japanese comic-book style LoRA I've seen, and it has a pleasing sort of US/UK 2010s 'amateur indie comic' look.

https://huggingface.co/EllaPriest45/MinimaxH3_Styles/tree/main

-> A Reddit post reporting apparent success with motion-transfer, by using a Minimax reference video converted to a DensePose sequence. This makes me wonder how Minimax would react to a greyscaled clown-pass render from a 3D figure animation, which would look similar... and might also solve the problem of DensePose not doing hands?

https://www.reddit.com/r/StableDiffusion/comments/1vrrrab/minimax_h3_is_seems_to_be_able_to_process/

https://blender.stackexchange.com/questions/102672/how-to-create-a-clown-pass-for-material-selection-in-photoshop ('what is a clown-pass?' visual example)

-> Yes, I'm aware of the new non-commercial ComfyUI MiniMax-H3 SPEED Sampler. But I see it requires his "MiniMax-H3 plugin"... which is "404 not found" on the link to it, and which doesn't exist on his repository (I poked around).

https://github.com/StanLukuvka/ComfyUI-MiniMax-H3-SPEED

-> And finally, a new big curated listing of all known Minimax H3 items. Includes a long list of the various Turbo LoRAs which have been produced to date.

https://github.com/wildminder/awesome-minimax-H3

Hello everyone

Want to get faster MiniMax H3 video generation without sacrificing quality? In this tutorial, I’m testing the new H3 LoRA together with Sage Attention, Sol Attention, and Spectrum nodes to find the best combination for speed and quality. The goal is to push MiniMax H3 as far as possible while cutting generation times by up to 2×, then upscale the results with LTX Upscaler to reach a stunning 2432 × 1344 (2K-class) resolution. By combining both H3 LoRA together with Sage Attention, Sol Attention, and Spectrum nodes I generated video at 0.8 megapixel using "**RTX3060 6GB 16GB RAM "**and I got

 13 minutes vs 41 minutes at 8 steps

 27 minutes vs 52 minutes at 20 steps

LTX 2.3 Upscaler 11 minutes to get 2432 × 1344 resolution

Workflow link

https://civitai.com/articles/34028/comfyui-tutorial-minimax-h3-4-steps-lora-upscaling-2x-faster-generation-best-settings-for-2k-ai

Video Tutorial link

https://youtu.be/ZUzeM9OEJ4Y

Hey all,

I built MiniMax H3 FlowDirector to streamline MiniMax H3 workflows and provide cleaner control over video generation flow without spaghetti wiring.

 Cleaner Pipelines: Replaces complex routing with a single, dedicated node.

 Better Motion Flow: Helps guide generation parameters more consistently.

 Plug & Play: Slots directly into your current H3 setups.

Example Workflow:

A drag-and-drop ⁠.json⁠ workflow is included in the repository so you can test it immediately.

Links:

 GitHub: https://github.com/AlonAshken/ComfyUI-MiniMaxH3-FlowDirector

 Comfy Registry: https://registry.comfy.org/publishers/vorpalblade/nodes/comfyui-minimaxh3-flowdirector

 ComfyUI-Manager: Search for ⁠FlowDirector⁠ or ⁠MiniMaxH3-FlowDirector⁠.

I did this after needing that option because I don’t have a ton of vram and customized a node that was first created by aitrepreneur (he’s awesome check his YouTube videos and stuff)

what I created works well for me but might not be perfect feel free to fork and change it however you want

Like some of ya'll I have been having fun using the H3 model to mess around with so I have been experimenting with using H3 model to be a consistent character generator which leverages multi image reference (up to 9), so I made a workflow which you can use 'less than ideal' images from google to build a consistent character and output a 360 character sheet to use as a reference sheet for future H3 generations.

The goal is to achieve high character consistency across future generations. I have tried my best to keep the workflow simple without too many custom nodes.

How it works:

• You input your images and describe them in the Input text section (A Prompt)
• The text is combined with a fixed prompt which spins the character (B Prompt)
• The video is generated at a slow speed with no hard cuts (only camera spin and pan) to maintain character consistency
• Image is assembled with optional character video and full individual frame output (if you want to use for future)

I have included a 6 panel WF and a 4 panel WF. The 4 panel works faster by generating 40% less frames.

Current Caveats:

• The model is quite slooooow. You are also generating 124 frames only to use 6. I have partly solved this by also uploading a 4 panel version.
• Speed ups (like Turbo LORAs) help with speed, but it hurts prompt adherence and quality slightly.
• Quality is limited, since it is a video model it is better at generating video than images. You can solve this by generating at a higher resolution at the tradeoff of longer gen times. You can also use the individually split frames as future references too.
• Details when using this character sheet as output for future generations on H3 may also be limited due to resolution also, I recommend you use this character sheet (for consistency) + other images close up angles (i.e clothing details/face) if doing close ups. If you are just doing a one off video you may possibly be better off not using this character sheet.

I have also included a modified B prompt to do Anime2Real since someone asked for it. Working on tidying it up a bit more.

Link to the 4 and 6 panel workflow can be found here: https://huggingface.co/PoopMan333/H3_Character_Sheet_Generator

Some notes I just remembered:

• You can increase the steps and it may improve your quality slightly.
• With the Turbo Loras enabled, prompt adherence sometimes suffers, but you may be able to get a good seed with another roll of the dice.
• Currently the B prompt specifies a "neutral A pose", please remove this if you want your character in a particular pose.
• You can use a few different shots of the same character to reinforce the 360 and get more accurate details right.
• Can be used for objects / props also, may require some changes to the B prompt.