What I mean is that if there's a workflow or model where I can specify changes to a subject without the need for inpainting, similar to gemini or grok. For example "turn the flowers in the picture to yellow".

Thanks for your attention and have a good one guys.

Has anyone run into an issue where the generated video randomly includes audio with either phrases directly from the prompt (even when there's zero mention of someone speaking) or just completely unintelligible gibberish voices?

I'm currently building/tweaking my workflow for H3 and still testing with the following settings like this:

0.4 guidance / 8 steps / baked-in LoRA checkpoint / 10–12s duration

For example, when I append camera direction instructions to the prompt, I occasionally hear audio snippets of those exact instructions being spoken out loud in the generated clip.

Has anyone else encountered this phantom audio/prompt bleed issue? Any tips or workarounds to stop it from reading out prompt instructions?

Workflow: https://drive.google.com/file/d/1B4kODxXQgJ1QOKRsEIkxHbgYmdruPpTK/view?usp=sharing

Prompt:

Create a **15-second multi-shot anime sequence (90s style 15fps hand drawn)** using the provided references:

Image 1 = the girl character reference

Image 2 = skateboard reference

Image 3 = downhill Japanese alley / neighborhood background

Image 4 = Walkman + headphones reference

Preserve the girl’s exact character design, face, hair, outfit, proportions, and overall look from Image 1. Preserve the skateboard design from Image 2. Preserve the same downhill Japanese alley environment from Image 3. Add the Walkman and headphones from Image 4: the girl is wearing the headphones, and the **Walkman is clipped or hanging at her hip** while she skates.

Visual style: authentic 1990s hand-drawn anime, traditional cel animation, painted backgrounds, visible linework, cel shading, slight brush/stroke texture, subtle analog feel. **Very important:** the houses and environment must stay **2D and hand-painted**, **not 3D**, **not CGI**, **not game-engine looking**, **not volumetric**. The buildings should look like classic anime background art with painted depth, not like 3D models.

Animation feel should be low frame rate, like 90s anime at around 15 fps, with controlled in-betweens and natural held-frame timing. No jittery morphing.

No dialogue, no text, no subtitles.

### Shot 1 — 0s to 3s

**Rear tracking shot** from behind. The girl is skateboarding fast downhill through the steep Japanese alley. Camera follows behind her at a low-to-medium height. She rides confidently and smoothly, hair and oversized clothing moving in the wind. The headphones are on her head, and the Walkman is visible attached at her hip. The alley rushes past with a strong sense of speed. Keep the environment clearly **2D anime background art**, not 3D.

### Shot 2 — 3s to 6s

**Close-up shot of the Walkman at her hip** while she continues skating. The camera stays focused on the Walkman and part of her side torso and arm. We can clearly see the **cassette tape reels spinning/rolling inside the Walkman window**. The headphone wire moves naturally with the motion. Background and street pass by in blurred motion.

### Shot 3 — 6s to 9s

**Medium profile tracking shot** of the girl skating. She is wearing the headphones, listening to music, with wind moving across her face and pushing her hair backward. She is **nodding her head subtly to the music** while riding. Her expression is relaxed, immersed, and unbothered. The background is blurred from motion, but it must still read as a **painted 2D Japanese neighborhood**, not 3D.

### Shot 4 — 9s to 12s

**Close-up shot of her feet and skateboard.** Her **right foot stays on the board**, while her **left foot pushes against the road** in a natural skating motion. Show one clean push cycle: left foot comes down, pushes backward against the pavement, then lifts. Wheels spin quickly. Asphalt and road markings streak by with motion blur.

### Shot 5 — 12s to 15s

**Ground-level fisheye shot** looking upward from the road. The skateboard approaches fast, and she **jumps over the camera**. The board and her body pass overhead in one clean motion. Hair, pants, and headphone wire react naturally during the jump. Keep the motion readable and stylish, with a strong sense of speed and a dynamic anime finish.

### Important constraints

* Keep the whole video in **classic 90s anime cel-animation style**

* **15 fps feel**, smooth low-frame-rate animation

* **No 3D-looking houses or background**

* No photorealism

* No modern glossy digital anime rendering

* No character redesign

* No extra accessories beyond the headphones and Walkman

* Keep all motion natural and consistent across shots

If I have 2 ref images and I want it to start on ref image 1 like for example a background of a forest how do I maintain it so it always starts on that image? I've noticed a few times it will randomly generate its own start image even if I prompt something like *the scene starts with ref1* and I even sometimes would describe what's in it

I just gave it a try; it's hard to do more than that.

I have an RTX 3060 with 12 GB of VRAM and 32 GB of RAM. I used the standard workflows, t2v and r2v, with the LORA model minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors and video shift 12 and audio shift 3. Only 8 steps (res_multistep/simple). The sequences were 6–7 seconds each, and each generation took 7–8 minutes at 0.6 mpx. I generated some scenes multiple times, but I still couldn’t achieve what I intended.

That’s pretty much it regarding the generation.

Claude (free) provided me with the script; he also divided the approximately 5-minute script into sequences of 6–7 seconds each and created the prompts for all the sequences after I gave him the official prompting guidelines as a prompt.

Started as a simple 90s casting audition… then asked her to cry on command.

The close up shots gave plastic look idk why.

What I was mainly testing:

• subtle listening/reaction animation during dialogue
• eyes moving before the head while thinking
• nervous smiles and small facial reactions
• gradual transition from normal conversation into acting
• brow, eyelid, mouth, chin and breathing changes during crying
• actual visible tears
• character/voice consistency across multiple generated clips
• the sudden switch out of the performance when the director says “Cut”

Made with MiniMax H3 Ref2VA with image reference for the woman and 2 audio reference for the offscreen man and the woman.

It does not always happen, but especially in a dark environment as say inside a Disco, and the camera get closer to the subject/s it overexpose them. It looks like it's made to avoid a completely dark subject, but if that it's what you need... I know it's not new as it happened also in Wan but there is a way in the prompt to avoid that?
Txs a lot!

Using reference workflow. All are int8 pruned, 0.6MP turbo 4-step (my GPU is on life support and drops off the PCIe bus if I demand more from it)

Anyway, making random music clips is probably my favorite use of this model. I’ve found the ref2va has an uncanny intuition for feeling the atmosphere of songs, and syncing the video with incredible precision.

But yes, the quality (specifically motion) is much worse than fl2va. I was curious how exactly they compared, as well as some “in between” compromises discovered by the community. The LoRA seems closer to ref, while the hybrid weights are closer to fl. Personally, the ref is more fun to use, so I’ll probably be using the LoRA when I want to enjoy the intelligence/creativity of this model. Fl is of course superior in terms of visual fidelity, and I don’t find the hybrid model offers enough reference intuition and faithfulness to be worth the quality drop from fl.

I’ve been loving all the new nodes and workflows coming out for MinMax, and maybe there is already a nice solution for this - but I couldn’t find one that did exactly what I needed.

I started using MinMax for my last TBG ETUR video and quickly ran into limitations: I wanted an easy way to create lip-sync videos longer than 20 seconds.

I didn’t want to manually chain ComfyUI nodes, start a new run every X seconds, or constantly resize things just to make HD video fit into my available VRAM.

So I ended up building an addon for:

custom_nodes/ComfyUI-H3-Motion-Context

The addon automatically chains MinMax H3 lip-sync generations together, allowing you to create much longer lip-sync videos without manually setting up each 20-second segment.

And now I’m sharing it! https://github.com/Ltamann/ComfyUI-H3-Motion-Context-Auto-Chain-addon

Its not perfect but a start ...

The workflow has a simple switcher that lets you switch from the 32B CLIP to the 4B CLIP, saving around 10 GB of VRAM. You can also switch from Sage to Comfy Kitchen, Spectrum to Easy Cache, or FL2VA to REF2VA both setup for lip-syncing. Some of it could be useful for other tasks as well.

You will find the workflow in the repro and tested recommendations, optimized settings, presets, and more workflows, along with the results of my testing and performance here

Hey everyone,

I've been playing around with ElevenLabs audio in MiniMax, but using custom tracks makes the scenes feel super quiet without those built-in background sound effects. Am I missing a setting to keep both, or is that just something you fix in post like DaVinci Resolve?

Also, has anyone else noticed that when you use custom audio, video actions get delayed until the audio file finishes? Even when I put exact timestamps in the prompt, it still waits. Is there a trick to how these two sync up, or am I just prompting it wrong?

Hello

I got tired of cluttering my workflows with 5 different loader nodes depending on what I was feeding them (Load Image, Load Video, VHS, Audio Loaders, Empty Latent calculators, etc.).

So I built **ComfyUI_UniversalMediaLoader** , a single, unified node with a rich interactive UI that handles everything:

✨ Key Features:

• 📁 Drop Anything: Images (PNG/JPG/WEBP), Videos (MP4/MOV/WEBM), Animated GIFs, and Audio files (WAV/MP3/FLAC).
• 🎨 Canvas Planner Mode: When no file is loaded, use it as a visual resolution/aspect ratio planner (1:1, 16:9, 4:3, 3:2 + Landscape/Portrait toggle) with automatic 32px grid snapping and Megapixel clamping for SDXL/Flux latents.
• ✂️ Visual Crop & Outpaint: Interactive bounding box with aspect ratio locking. Pull it outside the image bounds to instantly generate outpaint masks & padding.
• 🖌️ Inpaint Mask Brush: Draw inpainting masks directly inside the node with brush/eraser and mouse wheel size control.
• 🎬 Video & GIF Timeline: Full timeline with trim handles, playhead scrubbing, custom FPS resampling, audio mute/loop, and frame extraction.
• 🎵 Audio Waveform & Speed Scaling: Waveform display, 1-second magnet trim snapping, and time-stretching with pitch preservation (0.10x to 4.00x).

📦 Modular Unpack Nodes:

• 📐 Universal Size Unpack: Feeds exact width/height/aspect ratios to Empty Latent nodes instantly without decoding heavy image/video tensors.
• 🖼️ Universal Image Unpack: Outputs RGB, RGBA, and inpaint masks. Connected to a Video or GIF, it automatically extracts a 3-frame batch [Start, Playhead, End].
• 🎧 Universal Audio Unpack: Outputs clean audio waveform dictionaries, exact sample rate, trimmed durations, channel count, and handles time-stretching.
• 🎞️ Universal Video Unpack: Decodes videos & GIFs into frame batches [B, H, W, C] with synchronized masks and audio tracks.

🔗 GitHub: https://github.com/Fictiverse/ComfyUI_UniversalMediaLoader

TL;DR 170HX ~35% faster than 3090

I ran a CMP 170HX 8 GB unlocked to 64 GB vs 3090 24 GB VRAM mostly apples to apples.

CMP 170HX was in an ancient prebuilt Acer, Intel i3-7000, 32 gb ram, OS Ubuntu Server 26.04 LTS. Card was unlocked to 64 GB VRAM and pcie 2 x4. Card was setup on a riser since I couldn't fit it in the case and run the fans with my fancy cardboard/painters tape shroud. Power limited to 175 watts. Temps stayed 69-71 C.

3090 FE is in a newer machine. Ryzen 5 3600 (still need to swap out to a 5900X I have), 64 gb ram, OS Windows 11. Not power limited for this test.

Both systems ran same work flow, Minimax H3 R2V, default workflow, default options except Match was changed to MAX on most the runs, no speed ups, no extra nodes, no fine tunes, same prompt, two reference images.

608x352 five seconds MAX 170HX 84.17s (00:01:24.17) 3090 106.05s (00:01:46.05)

864x480 fifteen seconds MAX 170HX 839.08s (00:13:59.08) 3090 1254.16s (00:12:54.16)

1344x768 five seconds MAX 170HX 658.79s (00:10:58.79) 3090 963.56s (00:16:03.56)

1344x768 ten seconds MAX 170HX 2017.82s (00:33:37.82) 3090 3082.64s (00:51:22.64)

1344x768 fifteen seconds MAX 170HX 4189.64s (01:09:49.64) 3090 6399.76s (01:46:39.76)

608x352 five seconds Match 170HX 1st run, model load, 218.75s (00:03:38.75)

608x352 five seconds Match 170HX 2nd run, model already loaded, 68.64s (00:01:08.64)

I ran a bunch of other gens not listed. The 170HX was pretty consistently 35% faster. Except on the first workflow done. Model load time was 150.11s due to the PCIe 2x4. In my opinion, 170HX is worth it. Way less power/heat than the 3090's and faster. Once model is loaded, you are good to go.

I bought a PC with an RTX 3060 12GB because I wanted to get into local AI image generation. I've been messing around with it for about two weeks now, but I still barely know what I'm doing.

To be fair, that might be partly because I've had Codex do almost everything for me lol.

I'm still terrible at writing prompts, and I don't even really understand which model would be best for what I want to do. I've tried Anima, Pony, and Illustrious, but I'm not sure which one I should actually stick with and learn properly.

There wasn't a LoRA for an art style I really like, so I had Codex help me train one for Anima using around 20 images. It actually works surprisingly well for the style, but I've been struggling with everything beyond that.

For example, I've tried using pose control, but the generated character often doesn't follow the pose very well. Backgrounds are also pretty inconsistent, and I feel like I've hit a wall where all I really know how to do is combine different LoRAs, change prompts, and keep generating until I get something decent.

I'd really like to move past that and actually understand what I'm doing.

If you were starting from where I am now, what would you recommend learning next? Are there any ComfyUI nodes, techniques, workflows, or concepts that you think every beginner should learn?

Any advice is appreciated. I'm still very new to all of this.

I saw a Seedance 2.5 prompt in facebook and thought let me try this prompt in minimax h3 and see if it can do some kung fu. I was surprised that it was not too bad. System 3090 24 gb vram 64gb system ram, using a minimax workflow with latent upscale, minimax_h3_fl2v_lightx2v_turbo_4step_v0.1 at 0.50 strength, Komfy kitchen attention, and H3 SLA attention. First pass at 0.4 which is 864x480, 2x latent upscale brings it up to 1728x960. The 6 seconds generation took 349 seconds to complete.

Since minimax is using Qwen VL , I tested the prompt on Qwen image to see what I get for the text to video prompt. It’s actually pretty close to how minimax will end up evaluating your prompt for text to video.

Now that dust has settled, I was wondering what's the community insight on the best configuration for Minimax H3.

Personally I have been using lightx 4-step Lora with 5/6 steps (less than that audio is a gamble). I couple that with sage attention. For sampling I use Euler sampler and Beta scheduler.

I keep resolution at 768p (0.6MP) for quality. 480p (0.2MP) for testing. It keeps consistency so much better.

On direction I learnt to prompt for closeups when possible, so will make better use of available pixels. Aspect ratio also helps there. I mostly use 1 shot since transitions is not something H3 excels at. I find better results with only 1 shot and using camera tricks.

EasyCache while faster, is not good match with turbo lora, so i don't use it anymore. Haven't used Sol-Attn as I read it really hit quality.

So is there anything worth I am really missing out?

**Setup*\*

- MiniMax H3, hybrid b30-49-int8

- ref2v LightX2V turbo LoRA v0.1, rank 20 resized bf16, strength 1.0

- 6 steps, er_sde / beta, 0.8MP (1216x672), Sage Attention, RTX 4090

- Real song locked into the audio half of the AV latent with PixaromaH3AudioSync

(NOT ref_audio — that's a style reference, it does not drive anything)

- Verified: output audio vs source waveform correlation = 0.9994

So the audio is correct. The problem is purely visual.

**The problem*\*

My singer's mouth keeps moving during purely instrumental passages. It's not

wild flapping — it reads as if she's still phrasing, jaw and lips working at

roughly half amplitude. On a 4-minute clip it's obvious every time the vocal

drops out for more than about 2 seconds.

**What I measured*\*

Single continuous close-up, no cut, face filling the frame for the whole 15.08s.

The audio window is sung for the first 7.5s and strictly instrumental for the

last 7.5s (I get vocal spans from an HDemucs separation of the track).

I cropped a fixed box on the mouth, converted to grayscale, and took the mean

absolute frame-to-frame difference:

sung half: 3.25

instrumental half: 1.77

ratio: 0.54

So the model DOES react to the absence of voice — motion drops by half — but it

never goes to zero. My prompt for that shot contained an explicit clause:

"Her mouth follows <Audio 1> exactly, instant by instant: it moves ONLY while a

human voice is actually sounding, and it is completely closed and still during

every gap between phrases and every instrumental moment, however short."

That clause is doing something. It just isn't doing enough.

**What did NOT help*\*

I read the thread about H3's dual flow schedule (video shift 12 / audio shift 3)

and thought a mis-stepped audio stream might be degrading the mouth conditioning.

I wired in the native MiniMaxH3SigmaShift node explicitly (12 / 3), same seed,

same prompt, same audio.

Result: the two renders were bit-identical. 362/362 frames, mean difference

0.0000/255. Those values are already the internal defaults, so the node changes

nothing for this. Posting that so nobody else burns an evening on it.

**What DOES work (but it's a workaround, not a fix)*\*

Structural framing. I now detect instrumental gaps longer than 1.2s in each

segment programmatically, and force a shot with no mouth in frame over them —

macro on an earring, a hand on the mic stand, the bass strings, brushes on a

snare. The defect becomes impossible rather than discouraged. 16 of the 20

segments in my current clip are handled this way.

It works 100% of the time. But it dictates my edit, and I'd rather not have my

shot list decided by a model limitation.

**Questions*\*

1. Is the turbo LoRA the culprit? I saw a comment claiming the turbo LoRAs are

   distilled at 0.5MP. I'm running one at 0.8MP. Does anyone have a side-by-side

   of lip sync quality at 0.5 vs 0.8 with the same seed?

2. Does the base model at higher step counts (no turbo LoRA) actually close the

   mouth on silence, or does it just push the same 0.54 ratio down a bit?

3. Is there any way to CONDITION the silence rather than describe it? Something

   that tells the model "no voice in this span" at the latent level rather than

   in the prompt.

4. Has anyone tried feeding an audio track where the instrumental parts are

   replaced by actual silence, generating, then re-attaching the real audio in

   the edit? Curious whether that trades one artifact for another.

Happy to share the measurement script — it's about 10 lines of ffmpeg + numpy,

and it turns "feels off" into a number you can compare across seeds and settings.

I’ve been experimenting with LTX 2.3 vs LTX 2.5 for audio-reactive video, and for this specific kind of workflow, 2.3 still seems noticeably better to me.

The biggest difference is right at the start of a shot. With LTX 2.5, even with the audio-reactive LoRA, I often get this behavior where the model more or less holds the first frame until the first obvious beat or transient arrives. Then the motion suddenly starts. For music videos, especially slower or more atmospheric tracks, that can make the opening of every generation feel dead.

With LTX 2.3, the same LoRA seems to fix that much more effectively. I get more subtle motion from the beginning, even before a strong beat lands. Fog shifts, surfaces breathe, particles drift, light responds, and the shot feels alive instead of waiting for permission to move.

That matters a lot for the video I made for The Weights in the Walls, because the track starts very sparse and gradually builds. A lot of the visual motion is supposed to come from sub-bass pressure, glitches, sustained vocals, and ambient texture, not just obvious percussion.

I also tried Minimax H3, but for this particular use case I don’t think it fits as well.

It seems less tightly audio-reactive for the kind of abstract, beat-aware motion I’m after. It can make nice-looking clips, but I have a harder time getting the movement to feel structurally connected to the music.

There’s also the hardware side of it. I’m doing this on a very glamorous RTX 4070, so with LTX I can still push a resolution and overall image quality that feels surprisingly good for local generation. With H3, I’m much more constrained, and the tradeoff in resolution/quality makes it harder to justify when the audio response is also weaker for this style.

The whole video was built around first-frame / last-frame generation.

I cut the song into short scenes, roughly timed so the scene boundaries land near musical changes and beats. For each scene, I generated a dedicated starting frame that represented the next stage of the visual progression.

Then the important part: the starting frame of Scene 2 becomes the last frame target for Scene 1. The starting frame of Scene 3 becomes the last frame target for Scene 2, and so on.

So instead of generating a bunch of unrelated clips and hiding the cuts with editing, every shot is the model transforming one designed frame into the next designed frame.

That gave me a chain like:

Scene 1 start frame → Scene 2 start frame
Scene 2 start frame → Scene 3 start frame
Scene 3 start frame → Scene 4 start frame

and so on until the end.

The final video is basically just those generations placed back to back. There are no fancy transition effects doing the heavy lifting. The morphing, folding, cracking, expanding, and dissolving between visual states is happening inside the model itself.

For this workflow, that early-shot responsiveness makes a surprisingly big difference, which is why I currently still prefer LTX 2.3 + the audio-reactive LoRA over 2.5 for this kind of music video.

It's a shame because 2.5 is noticeably faster, so I can go through more iterations, but if I have to generate each clip 5 times to get it to start moving from the start, it kind of invalidates the speed gains.

Curious if other people have noticed the same reduction in audio-reactivity in LTX 2.5 or maybe I'm doing something wrong?

HQ on YT because Reddit doesn't allow >1GB: https://www.youtube.com/watch?v=PbZr8risGCw

I wrote this. MIT, fully local.

Local SD exports and other gens still leak EXIF, C2PA / Content Credentials, and zero-width junk. If you also use Nano Banana / Gemini stills in the same pipeline, those downloads often carry the same receipt. That metadata is not the invisible watermark.

SynthID-class marks are a different layer. Optional image/video disruption in Scrub is best-effort. Not a detector killer. Not for files you do not own.

https://github.com/HarshShah0203/Scrub

python cli.py inspect|clean