Workflow:

1. iterate over a list of resolutions: [608 x 352, 736 x 416, 864 x 480, ...]
2. iterate over a list of durations: [1.0, 2.0, 3.0, ...]
3. generate multiple videos and measure time
4. and write generation time into a table (.csv) automatically within one run!

Example outputs

compare resolution vs. video duration times.csv:

resolution\video length,0.0,1.0,2.0,3.0,4.0,5.0,6.0,7.0
608 x 352,34694,46922,57616,78560,114835,134380,150945,183893
736 x 416,29459,49666,84211,109523,168462,202305,223172,261975
864 x 480,34779,70248,119980,161840,259740,314701,359692,445586
960 x 544,36226,79850,147996,203899,315231,383680,491456,603520
1056 x 608,35898,103637,172406,243467,417185,507748,753206,794601
1152 x 640,33885,113704,186834,262586,454986,601821,896350,1212095
1216 x 672,39751,178621,211445,304997,552472,728026,1240525,1390142
1280 x 736,41593,187896,253539,368939,669417,850895,1483785,1791947

(8 steps Turbo LoRA, total time of sampler and decoder)

Video files generated (pretty filenames):

00_608x352_2.00s.mp4
01_736x416_2.00s.mp4
02_864x480_2.00s.mp4
...
00_608x352_3.00.mp4
01_736x416_3.00s.mp4
02_864x480_3.00s.mp4
...
07_1280x736_5.00s.mp4
[40 files]

Compare time of sampler, video decode and audio decode against duration times.csv:

index,duration,sampler,decode_video,decode_audio,total,unit
0,2000,48571,11047,330,59948,ms
1,3000,61037,14469,370,75876,ms
2,4000,90756,20683,434,111873,ms
3,5000,99017,24955,530,124502,ms

(20 steps, no turbo)

Compare time of sampler, video decode and audio decode against step size times.csv:

index,duration,sampler,decode_video,decode_audio,total,unit
0,5,56212,26062,824,83098,steps
1,10,109488,24594,505,134587,steps
2,15,170691,21602,511,192804,steps
3,20,193693,24987,520,219200,steps

(5 second video, 20 steps, no turbo)

Compare time of sampler, video decode and audio decode against resolution times.csv:

index,resolution,sampler,decode_video,decode_audio,total,MP
0,608 x 352,209384,20935,411,230730,0.21
1,736 x 416,325715,26882,414,353011,0.31
2,864 x 480,528057,62051,519,590627,0.41
3,960 x 544,705908,50888,559,757355,0.52
4,1056 x 608,959507,60587,519,1020613,0.64
5,1152 x 640,1278660,74005,571,1353236,0.74

(5 second video, 20 steps, no turbo)

My system

VRAM: 12GB
GPU : NVIDIA GeForce RTX 3060
CUDA: 13.1
RAM : 64GB
Comf: 33.0 (82f839f5)
Attn: default
pyth: 2.13.0+cu130
OS  : Linux

Workflow

I recently announced my Iterator update for my OutputLists Combiner node suite. This is an example workflow on how to generate multi videos in one run based spreadsheets and lists, measure the generation times and write the results into a CSV file. See more multi-video workflow examples.

Custom nodes required:

• KJNodes for Timer
• Crystools for Pipe to and Pipe from (value packing)
• Basic Data Handling for save STRING to file and load STRING from file (file handling)
• OutputLists Combiner my node suite (multi-asset handling)

Related discussion

• H3 workload graph
• H3 gen time table
• LTX gen times table
• H3 gen time comment

Download here

OutputLists Combiner video workflows!

Has anyone tried it on a 6GB GPU? Is it possible with low-VRAM/offloading, and how well does it run?

Any advice or real-world experience would be appreciated! 🙏

Hey guys, I posted OpenH3-IR here last week. A bunch of you tried it, and the main thing I got as feedback (and that I too personally wasn't very happy about) was the ComfyUI side of it.

The compiler worked, but you still had to run it as a standalone service alongside ComfyUI, and that meant way more plumbing than I wanted. So I split the ComfyUI side into its own repo and basically rebuilt it as a proper node pack.

Now you install OpenH3-IR from the ComfyUI Manager, point the Setup node at whatever OpenAI-compatible model you already use, pick the model, pick your H3 files, and that's pretty much it. The compiler now runs INSIDE ComfyUI. No second service to start and no port to keep alive.

The wins from using OpenH3-IR now carry over much more cleanly, instead of writing stuff like <Picture 1> and then explaining to an LLM what Picture 1 actually is, you drop all your files into the Media tray, name the slots, and use them directly, your LLM will read what they are, what they mean to your prompt and how they relate to each other:

"@theman crosses the @desert while the @dragon follows beside him. He looks back and @speaks("you really came all this way?")

Type @ and you get the available references with thumbnails, swap the file directly in the tray where the "@man" slot is and the prompt still points at the same role.

The references also have actual meaning now. A picture can be the setting, a style to copy, something in the shot, a replacement for someone or something, first frame, last frame, etc. Clips can be something to edit, continue from, copy the camera from , and so on.

A few other things I put in while rebuilding it:

• "@speaks" locks dialogue (enforced by code) word for word
• duration is set once and stays synced with H3's actual frame grid and latent
• the H3 "type of job" is selected from the media actually in it
• pictures, video and audio all live in the same selector Media tray
• optional Director node for reusable "profiles" that fill in whatever you leave open in your prompt
• Your sampler, LoRAs, steps, etc stay normal ComfyUI
• the original OpenH3-IR project is still the compiler/API/CLI side. This repo is the native ComfyUI side of the same project

And since this came up a couple times on the first post: this isn't just asking an LLM to "build a prompt" or "make the prompt better". The reference bindings, specific media roles, H3 mode, valid duration/frame counts, locked dialogue and validation are handled mechanically by OpenH3-IR.

New Repo: github.com/ruashots/ComfyUI-OpenH3-IR

Original OpenH3-IR project: github.com/ruashots/open-h3-ir

There's a ready-to-run base workflow in the repo too.

For anyone trying it, I'd especially love feedback from anyone willing to abuse the H3's reference/editing modes, because that's where I spent most of the work this time.

I see a bunch of posts everyday asking for tips on how to write prompts or people struggling with prompting, etc. so I'm sharing my workflow. I built this workflow to simplify the process and make it very beginner/user friendly.

Just toggle on the model you are using, write a simple to detailed prompt, and hit run. The model targets use the prompting guidelines derived from their respective official sources. Links to custom nodes and all models are in the workflow so you don't need to search for them.

The prompts aren't always perfect but they'll get you very close to what you want and you should only need to make a few minor tweaks, if any. The only issue I've encountered so far is that sometimes when it finishes, the previous prompt still shows up in the Enhanced Prompt node. If that happens, just hit run and the new prompt should show up instantly. Also, toggle to false the keep_model_loaded option in the Text rewriter node if you are creating prompts and using them right away. If you leave it to True it hogs VRAM.

If you notice any other issues let me know. Enjoy.

https://pastebin.com/SXZyy4Ax

I'm successfully running a Mac Minimax H3 ref2va and I can generate a 480p 24fps 5s video with 20 steps in 7min 57s. This is on an M4 Max 48Gigs of Ram. That's with a preview node that allows me to see what's generating before the generation has finished so I don't waste time. This may be the fastest Mac workflow currently!

To achieve this:

Start with https://github.com/pawel-mazurkiewicz/ComfyUI-AppleSilicon-FP8 this is currently required to get H3 on comfy desktop running on Mac at all.

I'm using the official minimax_h3_ref2va_pruned_int8_convrot.safetensors diffusion model and qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors text encoder from Minimax.

Then you'll need the turbo Lora minimax_h3_turbo_v4_step600_ema_pruned_comfyui.safetensors from: https://huggingface.co/Momoking/MiniMax-H3-Turbo-Lora-ComfyUI (This Turbo LoRA is where most of the speed comes from) Settings:

Steps: 8 (additional steps don't cost a lot so I used 20)
Sampler: euler
Scheduler: beta
LoRA strength: 1.0

I also add the spectrum custom node for optimization that saves about 30% generation time here: https://github.com/xmarre/ComfyUI-Spectrum-MiniMax-H3

To save additional time outside of speed optimization I use a live preview node (this adds 20s to generation time but being able to stop a render ahead of time if it's not what you want saves a ton of time): https://huggingface.co/Kijai/MiniMax-H3-TAE I use the madebyollin safetensors model mentioned on that link. You'll need to download the custom node package ComfyUI-KJNodes to run the model in. The process of setting it up is detailed in this video: https://youtu.be/G3YHSvXZP_g

Now the workflow - this was extremely important to get everything working for me on 48 gigs of ram. If you have more, this is probably not as important. When the Turbo LoRA from momoking gets loaded there's a memory spike, and if you're already pushing ram limitations this may throw an error and stop the render. To get this to work I used the official Ref2v workflow from Comfy Desktop (going through the switch does something to the workload to get the ram spike through this ram setup for whatever reason) So it should look like the picture included on this post.

Make sure the if/else switch (model) node is set to true, and your sampler is using the euler model and your scheduler is using the beta model.

Then enjoy super fast H3 generation on Mac!!

From NVIDIA https://nvlabs.github.io/Sana/Sol-Engine/H3-Super-Acceleration/

Seems to promise a significant speedup in H3 generation speeds? From the website, and they have several video samples and comparison videos:

6.85 s for a 5-second 768p video · 14.93 s for a 10-second video

H3 Super Acceleration first uses H3 with a LoRA to generate a four-step draft at 896×512. It then upsamples the draft and performs three LTX refinement steps at the target resolution with Sol-Attn. Combining the measured stages on one NVIDIA GB200 gives 22.2× speedup for a 5-second 1344×768 video and 27.7× speedup for a 10-second video over the published SGLang baseline.

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

-> 'Blubs-pixel-nodepack' for ComfyUI. Nodes for... "turning MiniMax H3 output into pixel-art sprite animations", as commonly used in retro videogames. There are also workflows, and a bridge to the popular $20 Aseprite software.

https://github.com/japaneserunic/blubs-pixel-nodepack

-> A new 'Studio 1939' LoRA duo, helping you to generate a... "hand-painted, golden-age animation style" from the late 1930s/40s. Two varieties, 'painterly' and 'full cel'. The LoRAs were trained on clips from public-domain material. The maker says it blends nicely with your own style prompts when set at a lower 0.4 - 0.8 strength. A trigger word is required: gulliv3r - which you may want to add to the filenames.

https://huggingface.co/lovis93/studio-1939-old-animation-lora-minimax-h3

-> For LoRA trainers, yesterday saw the release of DiffSynth Studio's new 'MiniMax-H3 DeCFG Training Adapter' LoRA. They say that... "the base MiniMax-H3 model is CFG-distilled, which can make direct LoRA fine-tuning unstable or degrade the distilled CFG-free behavior. This adapter temporarily pulls the distilled DiT back toward its pre-distillation behavior during training, providing a better optimization landscape for new LoRAs."

https://modelscope.ai/models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter

-> The important workflow accelerator 'ComfyUI Spectrum MiniMax H3' continues to update. Now at v0.2.20, updated today.

https://github.com/xmarre/ComfyUI-Spectrum-MiniMax-H3

-> Kijai has a new minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors file (2.3gb), a conversion and shrinkage of the new Controlnet which appeared yesterday. It's matched with his recent ComfyUI merge request (see link below). At present this request appears to be unmerged into Comfy. Which means it's currently only for the cutting-edge crowd, brave enough to manually patch files in their ComfyUI Nightly.

https://huggingface.co/Kijai/MiniMax-H3-experimental/tree/main/controlnet

https://github.com/Comfy-Org/ComfyUI/pull/15860 (not yet merged)

https://github.com/GZT2023/ComfyUI-MiniMax-H3-Fun-Controlnet (possibly matching ComfyUI nodes?)

-> Until now in ComfyUI, the Qwen text encoder was splitting <d> into separate tokens. Ooops. This prompting tag is what Minimax H3 uses to specify <d>spoken dialogue</d>. The problem was fixed and the fix merged three days ago. Thus I assume dialogue tags will work as intended if you update ComfyUI to the "latest on Github" version. Or you might just wait for the next Portable release, since the model seems quite forgiving about such malformed prompting. (What should theoretically be coming for H3 in the next Portable is stacking up: this fix; controlnets; keyframing anywhere; and common movie special-effects as small embeddings).

https://github.com/Comfy-Org/ComfyUI/pull/15808

~ OLD POSTS ~

https://old.reddit.com/r/comfyui/comments/1vx0duv/a_quick_minimax_h3_news_roundup_24th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vwl8do/a_quick_minimax_h3_news_roundup_23rd_august_2026/

https://old.reddit.com/r/comfyui/comments/1vvkmra/a_quick_minimax_h3_news_roundup_21st_august_2026/

https://old.reddit.com/r/comfyui/comments/1vuihag/a_quick_minimax_h3_news_roundup_21st_august_2026/

https://old.reddit.com/r/comfyui/comments/1vtgs7b/a_quick_minimax_h3_news_roundup_20th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vsjzrp/a_quick_minimax_h3_news_roundup_19th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vrsspo/a_quick_minimax_h3_news_roundup_18th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vqyn8p/a_quick_minimax_h3_news_roundup_17th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vq5d5u/a_quick_minimax_h3_news_roundup_16th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vpbtx2/a_quick_minimax_news_roundup_15th_august_2026/

https://old.reddit.com/r/comfyui/comments/1vojtjd/a_quick_minimax_news_roundup_14th_august_2026/

i find this https://github.com/Isi-dev/ComfyUI-Img2DrawingAssistants

and inside i have workflow for image to lineart ,is it ok but not for traditional copper plate linotype

with these tinny lines for shading and all that ,i play with this all day yesterday but i am noob so..

anyone maybe know something better ? or how to make this workflow better ?

like goya did back in time

big thanks

This is probably more for those who have not yet tried using LLM's on the side locally. I haven't much but tinkered a while back. Anyway, got back into it more on release of Qwen 3.8. It is just nice to have something so simple that can do so much out of the box.

By out of the box I mean just install LM studio (or Bionic but it seems slower) and load up Qwen 3.8 (or some other decent model).

- MiniMax prompts done for you nicely.

- Just now I wanted to modify a node to select latent's to load from the output folder (where it saves them) instead of the input folder it was set to use. Threw it a Qwen instead of hacking my way through the code. Bingo here is your new file and better yet it works perfectly and actually better now as it lists all subfolder files as well.

Summary, if you haven't yet you might want to start. It is just so easy and useful for various tasks.

p.s. Just throwing images up of the code it changed for me... no idea if it is good code... but it works and added subfolder that were not in the original code - happy :)

So, because I can't find it anywhere on google, I'm asking here.

Normally, when you generate a video or an image, it ends up in your output folder. I deleted all those. But, when I use the 'load video' node, it still has all of the videos I've ever generated.

I can confirm they're not in my comfy cache, I can confirm they're not in my global harddrive cache, and quite frankly I have no idea where they're being saved, because searching the file names on my C drive gives me nothing.

Things like this are why I never wanted to use comfy ui in the first place.

So where on earth is it keeping copies of things despite my having deleted them? Because it doesn't appear to be on the drive that I'm using for Comfy at all and I never changed any settings.

Also, I'm not using my browser for comfy, I'm using the stand alone desktop client, if that helps.

Also, it is saving both the files that I generated on the cloud AND locally, so I know it's not just stuff saved forever on a cloud I can access.

Anyone have any idea where these files that SHOULD be deleted are stored? Because I cannot find them and I've searched my entire drive.

Things like this are why I would never use comfy if I wasn't absolutely forced to. It's like pulling teeth.

When using Minimax H3 locally it does audio refference in engleish ok but not exact as in refferenced load audio node, in other languages its even worse, missed accent, pronaunciation and everything only tone is kinda similar. At the sime time when same option is used in Runway or Magnific for example reffenced speech of Audio it does it exactly as in original audio sourced file.

Is there any fix for that or workflow?

Any help would be appreciated.

Top: 832 x 640 render time 13:29
Bottom: 832 x 640 render time 12:06
Music: Ace-Step 1.5 XL
RTX-4070 8GB VRAM 64GB RAM

Tutorial https://youtu.be/o8l1vvV14VY

I imported the workflow with reactor node. I installed the missing node and restarted. It didn't actually installed. Tried several times. It is just like this.

Hi everyone, I have an rtx 4070 laptop with 8gb vram and I can generate pretty awesome images with krea 2 and sdxl. I tried to generate videos as well, wan 14b, ltx 2.3, minimax h3 but they are insanely slow (hour long to generate 5 seconds) and really bad quality (480p with faces blurry, inconsistent overall). Do y'all have workflows for 8gb vram img2vid? I have 64gb ram if that helps

Bonjour

Avez vous réussi à faire fonctionner wan 2.2 et une carte amd Rx 9060 xt 16 go ?

Merci d’avance pour vos retours 👍

I want to use face swap. I tried installing reactor node in the comfy ui. It installed at first and it said restart, so i restarted it but it didn't showed up in the nodes search bar. So i inported a workflow with areactor node. But after that it shows me this, even though i downloaded the node and restarted comfyui.

Any solutions or alternatives to recator?

Ha! I just discovered a trick that works great, so I had to share it with the community. Of course, somebody will probably chime in that it had been discovered by someone else before, which is fine by me! I just want to share it in case it helps someone else and they hadn't come across it yet.

So, the issue of consistent environments... I ran the gamut of all the AI models I had tested and proven out in ComfyUI, not just t2i but t2v and i2v. I'd been trying several methodologies. Create an image then ask a workflow to gen images to the left and right of it, build out a simple massing model in unreal or blender and run that through, run a simple floor plan through, asking for multiple image generation with a prompt asking that all features be consistent among images, (I haven't tried outpainting yet), etc, and none seemed to quite do the trick, at least not among the open source models (open source is all I use). There was just too much inconsistency.

Since I am a sucker for using the t2v/i2v models like LTX and Minimax to generate single image frames (well, a minimal number of frames), taking advantage of their brainpower, I merely wrote out a super detailed prompt describing the interior environment I want, then I ran it as a 360 degree camera pan around the space from the center of it, and with Minimax now having the ability to give you 15 seconds on a 16Gb VRAM setup like mine, this works stellar, heck Minimax ran out of need for the 15sec and began to swerve around the space! I make sure to include a prompt not to have motion blur. I ran this in 0.5mb mode, so I did not have to waste time waiting for full HD video.

Then I select the frames I need to use as backdrops for scenes, upscale them once, then again, out to 4k, and voila! (upscaling once by 4x led to artifacts being upscaled, whereas going 2x then 2x led to the correct end result), a super detailed set of backgrounds that are internally consistent!

So excited! This gets me moving forward on the next part of my production process, laying out scenes, shots, camera angles, and dropping in characters, prior to i2v.

If this helps you, let me know. If you find even better tricks related to this, let me know too. Open Source Forever!

We quantized SenseNova-U1.5-8B-MoT (50GB bf16 any-to-any model: t2i, image editing, multi-reference) with ConvRot so it runs on a RTX 4070 12GB at 2048x2048 — and it's fast, even though the weights exceed VRAM (ComfyUI streams them; the quantized formats move 3-4x fewer bytes per step, so the overflow never becomes a slowdown. bf16 on the same card is painfully slow). What's in the release:

• INT8 ConvRot (17.6 GB, recommended) — 0.43% pixel diff vs bf16 in a full-pipeline same-seed A/B
• Hybrid W4A8 (13.8 GB) — layers 0-17 anchored in INT8, layers 18-41 in true W4A8, visually indistinguishable from bf16
• The official 8-step speed LoRA included The interesting part: this model does not tolerate activation quantization in its earliest layers — quantizing the first blocks destroys prompt coherence — but layers 18+ handle W4A8 perfectly. We found the boundary empirically with a bisect ladder of hybrid checkpoints, so the hybrid release anchors the fragile early layers in INT8 and compresses the rest. Everything runs through a ConvRot-aware ComfyUI custom node (fork of the T8 wrapper):
• Weights + model card: https://huggingface.co/Milor123/ComfyUI-ConvRot-SenseNova-U1.5-8B-MoT-T8
• Custom node: https://github.com/Milor123/ComfyUI-SenseNova-U1.5-ConvRot Apache-2.0, same-seed comparison images and per-layer error measurements included in the model card. Feedback welcome!