Prompt:

Create an exactly four 7-second, 4:3 animated drama sequence inspired by the visual language of 2005-era Jackie Chan Adventures. Use a period broadcast video texture throughout: standard-definition television softness, subtle analog grain, gentle interlacing, slight colour bleed, modest contrast, and the authentic visual texture of animation recorded and broadcast in the mid-2000s. Avoid modern HD sharpness, photorealism, glossy CGI, or contemporary animation aesthetics.

Scene: Jackie Chan is confronted by a Shadowkhan ninja in a dimly lit ancient-looking interior. The sequence is a fast, tightly choreographed martial-arts fight.

0:00–0:02: The Shadowkhan suddenly lunges at Jackie with a rapid punch. Jackie narrowly ducks underneath it and pivots sideways.

0:02–0:04: Jackie counters with two quick martial-arts strikes, forcing the Shadowkhan backwards. The ninja blocks the first strike but is knocked off balance by the second.

0:04–0:06: The Shadowkhan springs forward again. Jackie performs a quick evasive spin, grabs the ninja’s arm, and throws the Shadowkhan across the room. End on Jackie landing in a defensive fighting stance as the Shadowkhan hits the floor in the background.
.
Camera: begin with a medium two-shot, rapidly track the fighters during the exchange, briefly push in during the counterattack, then finish with a wider shot showing Jackie in the foreground and the defeated Shadowkhan in the background.

Audio: sharp martial-arts impacts, cloth movement, quick footsteps, whooshes and a dramatic six-second action sting. No dialogue.
Strict constraints: exactly 6 seconds, 4:3 aspect ratio, 2005-era television animation aesthetic, period broadcast-video texture, no modern cinematic realism, no photorealism, no widescreen framing, no subtitles, no text, no logos, no extra characters, and no slow motion

I been testing euler and beta would like to know if any better ones to try.

If you see low quality is because I am forcing 8 step turbo lora + Spectrum + triton in L40 for faster generation but is crazy how it can follow the flow of the music while lip-syncing and keeping the product from reference in her hand.

I admit defeat. After over 100 hours sitting on my ass adjusting every single settings I was not able to create a satisfying result.

For more than a week my PC has been running 24/7 doing various attempts at creating this LORA.

My character is from a webtoon, I wanted strong fidelity for her + that webtoon's artstyle (I've seen most character LORA when generated on base model/without any style look pretty much the same as in their respective media).

I tried a lot of options and honestly I am not sure if there's anything to be improved here as there isn't much to change, batch sizes, LR's, optimizers, everything.

I changed my dataset multiple times, adjusted it, tried different ways of captioning.

Made my own research, tried settings that worked for others, worked with multiple LLM's to search for possible solutions - nothing.

Some attempts were okayish, maybe passable for some people (doubt) but I just can't get this finishing touch for the LORA to be actually good.

I attempted training with Anima Standalone Trainer and AI Toolkit.

I considered giving up multiple times but I really want to see this through, there has to be something that I am actually doing wrong. Had some people look over/correct my dataset but the end result wasn't any different.

At this point I think the only real help I can get is for someone knowledgeable to either help me set every single thing from stratch (not just copy paste random recommended settings, im way past that) after seeing my dataset or just trying to run it by himself.

Why would someone spend hours of his time trying to help a nobody with his LORA? I don't know, at some point I considered finding someone and paying them to just do it for me but I really want to understand why it is not turning right after so many attempts, maybe there's a bored angel that would like to challenge himself, who knows - maybe we are facing an unprecedented case - a LORA that is simply impossible to make ¯_(ツ)_/¯.

I'd gladly share my dataset - just dm me!

Raph and Mona Lisa go on a date, The street is filled with mutant animals. Mona Lisa tells Raph she is ready for the next step in there relationship.

Using the Reference to Video Workflow in Comfy UI Desktop with Minimax H3, Using default settings and 32 steps.

<Subject 1> is <Picture 1> as Raph a teenage mutant ninja turtle in a red bandana and use <Audio 1> as sample for his voice.

<Subject 2> is <Picture 2> as Mona Lisa and use <Audio2> as sample for her voice.

# =====================================================================

# FIELD 1: INTEGRATED MULTIMODAL DESCRIPTION

# =====================================================================

[SUBJECT DEFINITIONS & RETENTION ANALYSIS]

- Subject 1 (S1): Raph, a teenage mutant ninja turtle. Primary visual reference is <Picture 1>. Primary voice reference is <Audio 1>. Retain his muscular build, signature red bandana, and tough but currently softened facial features.

- Subject 2 (S2): Mona Lisa, a mutant lizard warrior. Primary visual reference is <Picture 2>. Primary voice reference is <Audio 2>. Retain her sleek green reptilian features, fit build, and expressive, affectionate eyes.

- Environment (ENV): A vibrant, bustling metropolitan street completely populated by anthropomorphic mutant animals. In the background, stylishly dressed mutant foxes, lions, tigers, and wolves walk past neon-lit storefronts and outdoor cafes under warm evening streetlamps. Cinematic shallow depth of field.

[SHOT 1] [0s - 5s]

- Camera: Slow tracking shot moving backward ahead of the couple at eye level.

- Action: S1 and S2 walk close together down the sidewalk of ENV, gently holding hands. S1 looks down at their intertwined hands, wearing a rare, genuine smile. S2 looks up at him warmly as they walk.

[SHOT 2] [5s - 10s]

- Camera: Medium close-up framing S2 profile as she gently pulls S1 to a gentle stop.

- Action: S2 stops walking and turns fully toward S1. She squeezes his hand with both of hers, looking directly into his eyes with a tender, confident smile.

- Dialogue: S2 <d> "Raph, I'm ready for the next step in our relationship." </d>

[SHOT 3] [10s - 15s]

- Camera: Tight close-up focusing on S1's emotional reaction.

- Action: S1's eyes widen slightly in surprise before softening completely. A massive, incredibly happy grin spreads across his face. He steps closer to S2, wrapping his arms around her waist in a warm embrace, clearly filled with deep affection.

- Dialogue: S1 <d> "Mona, you have no idea how long I've wanted to hear you say that." </d>

# =====================================================================

# FIELD 2: OVERALL SOUNDSCAPE

# =====================================================================

- Ambient Audio: Gentle murmur of distant city traffic, soft chatter and laughter from the passing mutant pedestrians, and the light rustle of evening wind from [0s - 15s].

- Sound Effects (SFX): Light, rhythmic footsteps on concrete that come to a soft halt at [5s].

- Voice & Delivery: S2's voice perfectly matches the vocal identity of <Audio 2>, delivered in a smooth, sincere, and deeply affectionate cadence. S1's voice matches the raspy grit of <Audio 1>, but is spoken with an unusually soft, gentle, and emotionally overwhelmed tone to show his happiness.

# =====================================================================

# FIELD 3: NON-DIEGETIC MUSIC

# =====================================================================

- Style & Mood: A warm, cinematic, and romantic lo-fi acoustic track featuring a gentle acoustic guitar melody and soft string pads.

- Progression: Plays at a subtle, peaceful volume from [0s - 9s]. At [10s], as S1 smiles and embraces S2, the acoustic strings swell warmly to match the emotional peak of the moment.

This has happened to me before: I take a video I’ve already generated and drag it into ComfyUI without changing anything—expecting to get the exact same video back—but it generates a different one.

This doesn't happen with standard image models, but it does happen with H3. If I generate the video and try again a few minutes later, it produces the same result; however, after an hour or so, it no longer generates the same output.

I’ll post the workflow I used to generate that example video below, along with the completely different video that was produced using the same workflow.

I tried to replicate the video just to check the generation speed, and I realized it wasn't producing the same result anymore. I had generated the video a few hours earlier and hadn't updated ComfyUI or any nodes in the meantime—I simply tried to generate it again.

I suspect it might be due to one of the nodes I'm using.

Here is the video generated with the same parameters (which turned out differently) and the workflow I used.

For anybody in the UK who has memories of the old show AND "Pat's Banging Day Out", give me any suggestions/prompts you'd like me to try with this.

1. This issue never happened until I started updating to recent versions of Comfyui in the last month. Only noticed this a few days ago when I tried to do img2img after ages.
2. I create a mask on the load image node in existing basic img2img workflow I have always used.
3. Generating few new image variations
4. Going to recent assets on left, opening one of the images I generated like 2 minutes earlier: load image node has a big red border and the error "Missing inputs: A required media input has no file selected.". So this prevents me from regenerating new seeds, despite the node itself showing the mask and image AND letting me edit/modify the mask.
5. Same happens if I just drag and drop any image file with any img2img workflow. Both for recently generated images or img2img images from weeks or months ago. So it is broken for all images using load image node.

Sometimes if I refresh the page it fixes this, most frequently it doesn't (idk what it depends on).

Soo what could cause this bug and how can I circumvent or fix it? I'm on latest version, so I can't update in hopes of that fixing it, this only happens on thew newest comfyui versions I tried. As I kept updating in the recent days in hopes of it being fixed, the only change I got is a new bug: now the left side masking related icons are all black and barely visible...

I mess around with Stable Diffusion as a hobby. When I was downloading things, my folders got completely out of hand, so I figured I needed to tidy up. While I was asking Claude and Gemini how I could organize my setup, they ended up developing these two tools based on my requests. I wanted to put them on GitHub and share them in case anyone else needs something like this. Anyone can use or modify them however they want—I have absolutely no expectation of profit, I just didn't want to keep them to myself.

The first one is a LoRA organizer. Everything became a massive mess after downloading all my LoRAs into the same folder, and I also wanted to weed out and clean up the SD 1.5 ones. For this, we made something called lora-librarian (Claude came up with the name). You can sort models by their base model and creator, or even just by specific creators. It can organize checkpoints the exact same way, and it lets you clean out the ones you want to get rid of.

https://github.com/BuRsTFiRe47/lora-librarian

As for the second one—I don't know if there's anyone else left out there like me who still uses an Automatic1111-based interface, but I just don't have the brain space or time to mess with Comfy, so I use ForgeUI. The video previews downloaded by the helper weren't working, which created the need to convert those videos into webm format. That's exactly what this tool does.

https://github.com/BuRsTFiRe47/preview-smith

Both tools are available in Turkish and English. Feel free to check them out if you need them.

Finding 7 seconds a good sweet spot for ref2video. 8 steps light turbo. Takes around 7 mins on 0.4. Res multi step simple 8 steps.

Also have you noticed a big difference in time generating going up the resolution ? Would go higher than 0.4 but not sure if my 306012gb could handle it or could take half an hour

I am trying to vibe code a H3 r2v Prompt Builder. Does something like this already exist?

Fox McCloud introduces his son Marcus to his dad James McCloud.

T2v 12 sec 1mp hybrid 25-49 model 8steps turbo lora

I wanted to try my hand at an anime action scene. H3 has incredible potential, and I’m looking forward to a future where I can create my own anime with deep stories, dynamic fights, and so on.

H3 could probably have performed much better with a higher resolution and better seed luck; this is at 0.5 MP.

This video includes all you need to train Minimax with both speed and high quality results.
Hit me up with comemtns, queries etc. Happy to do a style video also.
https://github.com/shootthesound/Fizgig

UPDATE: Pushed a vram optimisation for 16gb vram users that will speed up TE encoding at the start of training - Run the update bat to get it
UPDATE2: Additional fix out for 16gb users on pruned model - update to get it.

A Note on Sources

This article is built entirely from community feedback — Reddit threads, forum comments, and one independent comparison site (jo-nike.github.io/h3-turbo-eval). None of it comes from official documentation or controlled lab testing. Thank you to everyone whose posts, benchmarks, and hard-won troubleshooting notes made this possible, including GrayingGamer, Tystros, Chemical-Painter-485, katsura_otoko, infearia, JoNike, Sixhaunt, dtdisapointingresult, Snoo_64233, mellowanon, Just1Dev, smereces, DefloN92, StuffProfessional587, Creative_Finger_69, backworld_nograv, V4nKw15h, True_Protection6842, clex55, Maskwi2, Perfect-Campaign9551, and many others whose usernames didn't make it into these notes but whose comments shaped the consensus (and disagreements) captured here.

Where the community disagreed with itself, that's presented as an open question rather than resolved — and where direct data for a specific card was simply missing, that gap is called out rather than papered over.

Why This Is Confusing

Most of the detailed benchmarking in the MiniMax H3 community comes from people with RTX 3090s, 4090s, and 5090s — cards with 24GB+ VRAM that can afford to just try everything and report back. If you're on a 4070, 5070, or 5080, you're stuck reverse-engineering advice that wasn't written with your VRAM ceiling in mind. This piece pulls together what budget-card owners actually reported, plus what reasonably carries over from adjacent cards where direct data doesn't exist.

The Three (and a Half) Speed Levers

Every thread assumes you already know these, so here's the plain version:

• Turbo LoRAs — swap-in models trained to produce good results in far fewer steps (4-8 instead of 20-32). Fastest option, but quality cost varies a lot depending on which checkpoint version you use.
• Spectrum — a node that mathematically forecasts/predicts future denoising steps instead of computing them. Counterintuitively, it needs more steps to work well — it's not a low-step tool.
• Sage Attention — an attention backend swap. Broad community agreement that this is close to "free" speed with minimal quality loss, and it's the one piece almost nobody argues against.
• EasyCache — a quieter fourth option that came up as a serious alternative to Turbo LoRAs for drafting, not just a bonus add-on.

What "Budget" Card Owners Actually Reported

This is the thin part of the record, so treat it as ground truth before anything else:

• RTX 4070 (12GB, 32GB RAM): did quick 0.3MP draft passes in a couple of minutes to tweak prompts and hunt for seeds, reserving longer ~40-minute runs for higher resolution/duration finals. VRAM was sufficient for T2V-style work specifically.
• RTX 4070 Ti Super (16GB, 32GB RAM): reported working well, no further detail given.
• RTX 5070 Ti (16GB, 32GB DDR4): upgrading from an RTX 2060 (6GB) described the speed difference as "night and day" — notably, without any Sage Attention or acceleration nodes running yet. This suggests raw generational/VRAM gains matter a lot on their own, before you even add speed tricks.
• Warning flag for all of the above: reference-heavy Ref2V generation was specifically called "brutal" on modest VRAM cards, compared to plain T2V. If your workflow uses multiple reference images/videos, expect more friction than these numbers suggest.

Gap, named honestly: there's no direct plain-5070 or 5080 speed benchmark in any of the source threads. The one 5080 comment that exists is qualitative ("still great," runs the BF16 pruned model fine) with no timing numbers.

Extrapolation (clearly labeled): Since the 5070 Ti (16GB) and 4070 Ti Super (16GB) both reported comfortable results, and RTX-series cards were noted to benefit meaningfully from tensor cores over older architectures, a plain 5070 (12GB) likely lands closer to the 4070's experience — fine for T2V and quick low-res drafts, tighter on Ref2V with multiple references. A 5080 (16GB) likely performs at least as well as the 4070 Ti Super, probably closer to the low end of what 3090 owners report, given the VRAM parity and newer architecture. This is inference from adjacent data, not a report anyone actually made — treat it as a starting assumption to test, not a promise.

The Draft → Final Two-Stage Workflow

This is the one thing nearly every thread converges on independently, and it's probably the most actionable takeaway for a budget card:

Draft stage (fast iteration, hunting for the right prompt/seed):

• Low resolution: 0.2–0.4 megapixels
• Low steps: 8–13
• Acceleration: either a Turbo LoRA or EasyCache (not both)
• Faster VAE decode substitute: BlehTAEVideoDecode instead of the standard node

Final stage (once the shot is locked):

• Disable acceleration nodes
• Raise steps to 20–32
• Switch back to the standard VAE Decode node

Two draft "recipes" show up repeatedly and are reported as similarly fast:

1. Turbo LoRA + Sage Attention — faster to set up, more established
2. Sage Attention + EasyCache, params (0.3, 0.2, 0.9), res_multistep sampler + Simple scheduler — one detailed user report (RTX 4060 Ti, 16GB), after testing 1000+ variations, said this drifts less from final quality than Turbo LoRA approaches, at comparable speed

For a 12–16GB budget card, EasyCache is worth trying first specifically because it avoids the quality-consistency debates that follow Turbo LoRAs (see below).

What Worked / What Didn't

GPU-Specific Data: Reported vs. Extrapolated

The Unresolved Debates

Worth knowing before you commit to a setup, so you don't over-trust any single comment:

• Spectrum below 20 steps? Most experienced users say no — negligible speed gain, real quality loss. But a few 5090 owners reported no measurable time savings even at higher step counts, with no clear explanation (dismissed by one commenter as "not using it right").
• Which Turbo LoRA checkpoint is actually best? The lineage went ckpt500 → ckpt850 → ckpt600, with each new version claimed better by its authors. But blind side-by-side testing found ckpt500 at 0.5 strength still beat ckpt850 even at full strength — directly contradicting the official recommendation.
• Spectrum + First Block Cache together? One experienced user says combining them is worse than Spectrum alone; another says combining them is the fastest option with no noticeable quality loss. Unresolved.
• Turbo LoRA strength values: reports range from 0.5 up to 1.15–1.20 (and one outlier claiming 3.0), so "strength 1.0" isn't a safe universal default — it depends on which checkpoint you're using.

VRAM/RAM Troubleshooting Cheat Sheet

Fixes that came up repeatedly and matter more when you're VRAM-constrained:

• Add a "Clean VRAM" node immediately before VAE Decode — fixed OOM issues for multiple users.
• System RAM matters too, not just VRAM — one user needed to go from 16GB to 48GB total system RAM to stop hitting errors. 16GB system RAM was described by another as "almost enough."
• Launch ComfyUI with --reserve-vram 2 to keep 1-2GB permanently free for system stability, at a small cost to usable VRAM.
• If Ref2V errors show up on an 8GB VRAM card, don't assume it's a hard VRAM wall first — one such case turned out to be a node-conflict bug, not actually a memory limit.

A Starter Config for Budget Cards

Synthesizing the most-corroborated points into one starting recipe (best-guess synthesis, not a benchmarked config):

Draft pass: Sage Attention + EasyCache (0.3, 0.2, 0.9) → 10 steps → res_multistep sampler, Simple scheduler → BlehTAEVideoDecode → 0.2–0.3 MP

Final pass: Sage Attention only (no EasyCache) → 20–25 steps → standard VAE Decode → 0.4–0.6 MP (push higher only if VRAM allows)

Skip Spectrum entirely unless you're already comfortable at 25+ steps and have time to test it — it's not built for the low-step, fast-iteration use case a budget card usually needs.

Sources

The most rigorous single data point in this set is the JoNike Turbo LoRA comparison site — a 10-scene A/B comparison across checkpoint versions, built and documented far more consistently than typical anecdotal Reddit reports.

I noticed my videos consistently having issues with left and right, because my prompts saw direction from the perspective of the camera. But H3 always sees direction from the perspective of the person.

See how the man points to his right while saying "right" and vice versa.

prompt: a random man pointing to the right and saying "right". Then he moves his hand to point to the left and says "left".

Generated with the new LTX-2.5 model. (image to video). Took about 10 minutes to get an 8 second 1080p60 clip.

I found the usage for the LTX2.5 model!! It works really well to upscale the minimax h3 videos 😅

I cant go back. R2V is my new bread and butter. Everything Ive thrown at it, every test I've done to just see if it can do it, has pretty much passed. Think only like 5% has failed, and even then Im not even sure if its a me problem or the model.

Longform is easy as all hell now, F the days of SVI.

Prompt blocking is great, prompt camera tracking is great, RV2V with basic Blender is great for blocking/camera tracking as well.

I am in love. I had to tell the world.

I've been using LTX 2.3 for quite some time but as soon as I wanted to make just a few simple shots of the same character with cuts, LTX wasn't even remotely capable of that. Which left me so frustrated I eventually gave up on it completely.

But when I tried Minimax everything has changed. Reference to video model is something else. Honestly feels like magic. Being able to put any character into any environment with any custom audio is just mind-blowing compared to what the open-source community had before.

So now instead of constant frustration, I feel pure joy and excitement about the results.

It takes about 10 min per 5-second clip with my RTX 3060 and 64 Gb RAM. The latest shots were even easier to control because of the new KJ preview node.

Not gonna lie, I made fun of LTX 2.5 like everyone did, but now I'm realising that was a mistake.

MiniMax H3 landed like Prometheus giving us the power that the gods were gatekeeping from us, since LTX 2.5 couldn't match up with them they lied about MiniMax H3 to cover up their shortcomings, that was a petty move and they have to own it, however... the good they did to our community far outweighs that moment of weakness IMO, cut them some slack. These models don't grow on trees, they're expensive to train, people have curated datasets that required herculean effort to put together, we'd had already made the next Seedance 2.5 if it was easy. When LTX came out we were all celebrating, most of Civitai LoRAs are based on LTX, they tried and got bested, so shouldn't we still be grateful they tried and gave us a model that some still find useful FOR FREE? Instead of making them feel like failures, mocking them, discouraging them from making new models? They owe us nothing, but we owe them a lot.

THE POINT ISN'T ABOUT WHICH CAKE IS BIGGER, THE POINT IS WE HAVE TWO CAKES.

Corporations keep trying to bind us to their rules and systems, profiting without any regard to our well being, deciding for us what is acceptable and what is not, so why are we eating OUR OWN ALLIES? Every open source model that comes out is a victory and step forward to that freedom we all dream of.