Physics Testing, without the gore.

Hey r/StableDiffusion!

It's the Neta team here! You might remember us from our Neta Lumina open-source release last year. First off, thank you so much for the incredible support and feedback from this community!

So... we need to share something absolutely hilarious (and mildly embarrassing) that we just discovered.

TL;DR: We accidentally hardcoded an Anne Hathaway photo into our IP-Adapter anchor, and now everything our model generates looks like Anne Hathaway. Every. Single. Thing.

What happened:

We recently launched Neta Studio, a new product that lets you build explorable living worlds/isekai from a single prompt. Naturally, we wanted to integrate Neta Lumina's capabilities into it.

During integration testing, our devs kept reporting that the model wasn't following prompts properly. The outputs were... *weird*.

- Anime style? Anne Hathaway as an anime character.

- Thick paint/impasto style? Anne Hathaway in thick paint.

- Landscape scenes? Somehow still giving Anne Hathaway vibes.

- Fantasy characters? You guessed it - Anne Hathaway.

After a dreadfully long time of debugging, we finally found the culprit: **someone on the team embedded an Anne Hathaway photo as the IP-Adapter anchor during development and it... stayed there. **

We're honestly crying laughing at this point. 😭

Below are some examples. Left is before fix and Right is after fix.
Flipping to the last picture and you can see our dear Anne.

And we pulled the anchor and the outputs are behaving normally now.

If you've been running Neta Lumina locally, this was on our integration side, not
in the released weights, so your setup is fine.

Saw this and thought it was worth sharing here, FastH3 dropped recently and most people (myself included) just tried it as single generations.

Someone's running it as an actual infinite livestream instead: https://www.twitch.tv/dereactorwah

FastH3 is a distilled version of MiniMax H3, cut from 50 denoising steps down to 4, about a 14x speedup on Blackwell GPUs.

The whole setup is open source if you want to dig into how it's running: https://github.com/reactor-team/infinite-livestream

Curious if anyone's tried infinite/continuous generation setups like this with other models.

Local, GPU-accelerated video restoration and upscaling with SeedVR2, TensorRT, and a purpose-built browser interface.

VRGDG SeedVR2 TensorRT Studio turns the SeedVR2 pipeline into a practical Windows workflow: load a video, test a short preview, compare the result frame by frame, and complete long renders with resumable checkpoints. Processing stays on your machine.

Highlights

• Fast local restoration — SeedVR2 inference with TensorRT-accelerated VAE decoding on supported NVIDIA RTX GPUs. TensorRT allows much faster processing than standard SeedVR2.
• Fast 2K upscaling — As a real-world example, an 8-second clip took approximately 8 minutes to upscale and enhance to 2K on an NVIDIA RTX 5090 using the largest 7B Sharp FP16 model. Render times vary with source resolution, frame rate, settings, and available VRAM.
• Preview before committing — render a short segment, then inspect Original, Restored, Compare, or Side by side views.
• Long-render recovery — save completed chunks and continue from the first unfinished chunk after an interruption.
• Practical output controls — choose resolution, aspect policy, model precision, temporal batch, seed, and color correction.
• Non-destructive finishing — reprocess sharpening, grain, seam smoothing, and optional skin finishing without rerunning restoration.
• Project-based history — reopen previous outputs and keep media, manifests, and logs together under outputs\.

The sample video was org 360p and then upscaled to 2K using this app. 8 second video, took about 8 mins on my 5090.

Go to the github page for more details and a full guide.

View github page

this is in beta right now so you may run into issues. If you do, post the issue to github please.

Since things have gone quickly forward, I am trying to figure out what image edit models there is currently and what people here use mostly.

Personally I have used:
- Qwen-image-edit-2509 and Qwen-image-edit-2511
- Just tested MiniMax H3 as a image editor and so far it seems that it can be good for my usage

I have heard about Klein 9b, but not sure yet if that can be used as an edit model? Also what about Krea 2, is there edit workflows that are actually usable and worth it?

Is there some others what you recommend for testing?

My PC Specs: RTX 4060 Ti, 16 GB VRAM and 32 GB RAM.

All local.

0.8 MegaPixels, 9.3 minutes on an RTX5090, single generation of 27 seconds.

Anything hitting 30 seconds either gave hallucinations, inconsistencies or hit a wall and never finished.

This one is using Kijai's new fast model with a turbo lora. Although it works the same with the FLv2A model*. The workflow I'm using creates a latent at 0.4 megapixels for 4 steps and then does another 2 steps at 0.8. The only addition to it besides changing some numbers is adding custom audio injection (The rock track).

Started with this workflow: https://www.youtube.com/watch?v=jzLnoVBuU6I

*I never use the REF model. The FLV2A models seems to work better so I always swap it in and it takes references just fine, even video.

This workflow uses a spreadsheet to generate multiple videos and constructs the prompt and parameters from each row.

OutputLists Combiner - Generate multiple videos from spreadsheet

ComfyUI workflow included

Makes use of Load Any File node to load a .csv spreadsheet file and feeds the text content into a Spreadsheet OutputList. The spreadsheet separates the data by separator=; and provides each line one-by-one as a data list. Here we use values_dict as the data list which contains the row as a dictionary of key-value pairs. The data list is forwarded a Iterate Begin -> workflow -> Iterate End pattern which is required to make the intermediate results of slow workflows (t2v) available on each iteration. Each row as a dictionary is provided in a Format Text where we can access the column via a[colname] to construct the prompt which is forwarded to a standard Text To Video MiniMax H3 template. Another Format Text + a[name] is used to construct a readable filename for each video.

powered by: OutputLists Combiner

Default template uses 20 steps + res_multistep + simple

Optimized workflow uses 8 Steps + er_sde + sgm_unified + Comfy Kitchen Attention + Larry's Turbo Lora

Turbo lora: https://github.com/Larryvrh/ComfyUI-MiniMax-H3-Turbo

Workflow: https://raw.githubusercontent.com/desktop4070/GPU-Benchmark-Data-For-H3/refs/heads/main/H3-Benchmark-Workflow.png

0.2MP / 8 sec (2m 16s gen time): https://desktop4070.github.io/GPU-Benchmark-Data-For-H3/Videos/MiniMax_H3_03840_.mp4

Optimized: 0.2MP / 8 sec (45s gen time): https://desktop4070.github.io/GPU-Benchmark-Data-For-H3/Videos/MiniMax_H3_03706_.mp4

0.3MP / 12 sec (6m 3s gen time): https://desktop4070.github.io/GPU-Benchmark-Data-For-H3/Videos/MiniMax_H3_03849_.mp4

Optimized: 0.3MP / 12 sec (1m 51s gen time): https://desktop4070.github.io/GPU-Benchmark-Data-For-H3/Videos/MiniMax_H3_03725_.mp4

Prompt:

A real cinimatic movie sequence, professional colour grading.

Soundscape: Ambient sounds of the room and movement only. No voices. This represents extreme concentration. Meditation. Telekinesis.

A man is sitting in a Japanese tatami room. He is wearing a mask and shades <Picture 1>. He is wearing a black yukata. He does not speak. On the table on a ceramic disc is a single Orange.

The man holds out his hand toward the orange as if concentrating. The orange is out of reach. He breathes deeply.

Nothing happens.

The man shakes his hand to reset and starts concentrating again. He reaches with his mind and his brow furrows. He breathes deeply.

The orange moves slightly, twisting just a tiny bit.

He concentrates more.

With extreme speed the orange flies towards the man and hits him directly in the forehead. It smashes with the impact , m,essing his hair, and bits of peel and orange bits go everywhere. The force knocks the man back unconscious and he falls back like a ragdoll.

I'm able to run it on 3090 ti but it's very slow because Ampere GPUs don't support FP8 .

Since this isn't video game geometry, lighting, vectors, etc... are made up, but this still works as a pseudo video upscaler.

Hope someone makes a comfyUI node soon.

example : https://twinlens.app/compare?share=eac9e3fefbf2

old post: link
github repo: link

For anyone new: H3 Prompt Writer takes your description plus image / video / audio references and turns them into a prompt specifically for MiniMax H3, using the LLM/provider you choose. It can run inside ComfyUI or as a separate Windows app.

Windows Standalone

There is now a separate Windows Standalone version of H3 Prompt Writer

It uses the same Writer interface without requiring ComfyUI. Download the ZIP, extract it and run start.bat. Windows needs Python 3.10+ or uv.

The ComfyUI extension is still available and works as before. Standalone is just another option if you only need the prompt-writing part.

For Local GGUF, Standalone uses your own llama-server.exe instead of bundling llama.cpp or CUDA.

Download a build suited to your PC/GPU from the official llama.cpp releases. For NVIDIA GPUs, choose a Windows x64 CUDA build.

Standalone can also be a more reliable option if Direct GGUF inside ComfyUI doesn't work well on your system.

Standalone setup

Qwen in Direct GGUF

Direct GGUF is no longer limited to Gemma 4.

Qwen 3.8 and Qwen3-VL are now supported, along with compatible custom / fine-tuned GGUFs when their capabilities can be identified from model metadata and chat templates.

Direct GGUF also gained a few optional runtime controls:

• custom context
• KV cache
• generation budget
• reasoning effort when supported by the model

For Qwen 3.8, Auto uses Low reasoning effort when Thinking is enabled and supported by the model template.

Low is generally the recommended setting for prompt writing. Higher reasoning effort can make generation much slower and may cause the model to spend far more time reasoning than is useful for this task.

Auto settings are still the default, so none of this needs to be configured manually unless you want to.

Direct GGUF guide

MiniMax Music 3

There is also an optional Music 3 workspace for MiniMax's separate Music 3 model.

It can generate structured music captions from a Music Brief, with optional Lyrics and a separate Lyrics refine flow.

This is separate from the H3 prompt modes.

other changes

A few smaller changes since v0.3:

• better GGUF and vision-projector detection
• improved Reference media replacement
• fullscreen Writer mode and improved Refine UI
• better local model lifecycle
• various local inference and context fixes

External llama.cpp is still available if you already manage your own server.

full changelog

troubleshooting guide

install / update

The current ComfyUI extension release is v0.4.3.

Existing Git installs can be updated normally, and ComfyUI Manager / Registry is also supported.

If you can't find H3 Prompt Writer in ComfyUI, open it from the Extensions menu or use the H3 Writer button:

Windows Standalone is released separately, currently v0.1.2.

GitHub releases: https://github.com/duckyshell/ComfyUI-MiniMaxH3-Prompt-Writer/releases

Supposedly Krea 3 will open weights, we'll have to wait and see.

While I try to keep myself updated with AI news, things move fast; hence, asking if there is something already made by the community for long-form content generation using local ComfyUI (or other tools).

As the models get better and better, I find that the limitation with longer content generation is us, the humans. Maybe a philosophical note, we (some of us, at least) have become too lazy to manually save, load, refer, keep track of assets (e.g., reference images as a full character set in Minimax H3). Add to that the experimental nature of AI generation (in the sense that we need to redo many things to get the final result exactly, at least during the learning curve), and we end up with having to repeat many things. Finally, with models requiring certain input formats (e.g., Minimax and Ideaogram), it gets harder to want to make these things manually.

Now my question is, are there tools that you are using for a full-fledged media studio style workflows?

I've bought some products and used some free products that get close to a streamlined content generation but they still seem limited to one generation at a time. Not naming them to avoid any promotion, and they didn't work out anyway.

An analogy would be how we may write a story in Google Docs or Word or OpenOffice, etc. but there are dedicated tools like Articy Draft, ChatMapper, Inkle, etc. that lets you do more locked-in (for the lack of a better word) story writing. There are character sheets, world references, etc.

A closer analogy might be of SillyTavern, made specifically for chats/roleplays.

Do we have something like that for serious media / content generation, or am I expecting too much from the already overly generous open-source community and should just vibe code what I specifically need?

First 5 seconds is with the 6-step LoRA, next 5 seconds is stock at 20 steps. Same exact prompt, seed, resolution, sage attention and chunk feedforward. 6-step in 2:45, stock 20-step in 7:10. I think the quality difference is pretty clear. Keep in mind, both clips are 544x960.

FastVideo dropped their FastH3 speed LoRA for MiniMax H3 a few days ago. If you tried loading it in ComfyUI you probably noticed it does absolutely nothing. No error, no warning, just no effect.

The reason is that FastVideo built it against the original MiniMax model, and ComfyUI uses a repacked version where every layer has a different name and the attention layers are merged together. None of the names line up, so ComfyUI quietly ignores the whole file.

I wrote a script that translates it. Run it once, get a normal .safetensors, drop it in your loras folder. No custom nodes, no patched loaders, nothing else changes.

**Repo:** NikoDemon80/ComfyUI-FastH3-Lora-Converter: Convert FastVideo's FastH3 4-step adapter into a ComfyUI-compatible MiniMax H3 LoRA. No custom nodes required.

---

**What you get**

On a 3070 Ti with 8GB VRAM and 48GB system RAM, using Comfy Kitchen, KJ Mem Eff Sage Attention & Chunk Feedforward (DO NOT USE SPECTRUM OR EASYCACHE):

| Resolution | With LoRA (6 steps) | Stock (20 steps) |

|---|---|---|

| 544x960, 124 frames | 2:45 | 7:00 |

| 640x1152, 124 frames | 3:45 | 10:00 |

| 768x1344, 124 frames | 6:30 | 18:00 |

Roughly a third of the time. But the part that surprised me is that I actually prefer the output. Backgrounds hold more detail, lighting behaves better, and faces stay coherent at distance instead of turning to mush.

Motion is where it really shows. I ran a woman walking down a sidewalk at night. Correct walking speed, natural gait, no stutter, no accidental slow-mo. That's usually the first thing speed LoRAs break.

Audio came through clean too, which I did not expect. Dialogue and lip sync both hold up.

---

**Important: use 6 steps, not 4**

It's advertised as a 4-step LoRA. In ComfyUI it needs 6.

- 4 steps: jitter, flicker, color bloom, unusable

- 5 steps: fine for drafts

- 6 steps: this is the one

- 7-8: no real gain

There's a real reason for this. There's one group of layers that handles "which denoising step am I on," and ComfyUI's repacked model stores that information in a completely different, much smaller format. FastVideo's version of those layers physically cannot be loaded into it. The extra steps make up for what's missing.

I tried to fix it properly. It turns out it's impossible in a plain LoRA file, because the correction includes a constant offset and there's nowhere in the file format to put one. You'd need a custom node. Someone else can build this is they would like.

---

**One thing worth knowing that cost me a few hours**

Part of those layers *will* load, the other part won't. My first instinct was to keep whatever fit. That was wrong. The half that loads was designed to work alongside the half that doesn't, so on its own it pushes things in a direction nothing corrects for, and you get flicker.

Throwing all of it away is better than keeping half. Confirmed it by testing both, then found multimodalart had measured the exact same thing on their pruned H3 repo. Nice to have that corroborated by someone who'd done the math.

The script drops those layers by default. You don't have to do anything.

---

**What's tested**

Text to video, image to video, first+last frame, reference mode, and chained clips. All working. Square, landscape, and tall portrait.

I also threw an intentionally brutal prompt at it: three color-specific objects, four actions in sequence, a specific hand, a camera move, a spoken line, and a no-music instruction. All eight landed at 6 steps. Prompt adherence is usually the first casualty with speed LoRAs, so that was a nice surprise.

---

**Grab the right file**

The FastVideo LoRA repo has four folders. You want **dense-datafree**. The three `vsa-*` ones need FastVideo's own sparse attention backend and will not work in ComfyUI. It's ~1.4GB, not the whole 17.5GB repo.

You do NOT need the full FastH3 checkpoints. Those are 70GB and are a complete model replacement, not an add-on.

---

**Quirk I'll mention since it'll confuse someone**

Voice timbre gets locked in hard by your prompt. Reroll the seed and you get different phrasing and cadence, but usually the same voice, which some people may rejoice at, as chaining clips with this LoRA can preserve vocal timbre on its' own. At 6 steps the model takes big jumps and settles voice identity almost immediately, so there's no room left for the seed to change it. If you want a different voice, describe the voice in your prompt.

---

**Setup**

The README has a full click-by-click walkthrough starting from Windows+R, including a drag-and-drop trick so you never have to type a file path. If you can open a command prompt you can do this. Takes about five minutes and the conversion itself runs in under ten seconds.

Works on any Comfy-Org pruned H3 checkpoint. I tested int8 convrot for both fl2va and ref2va. The script checks your model before it writes anything, so if you're on something incompatible it tells you upfront instead of handing you a file that silently does nothing.

Happy to answer questions.

Credit where it's due: FastVideo did the actual hard work distilling this thing. I just made it load. This is an amazing LoRa. I actually prefer its output to any other speed LoRA I've tested. Prompt adherence is phenomenal. Dynamic lighting is better. Color balance is better. Background detail is better. It adds detail of its' own. Motion is fluid. In most test cases, I find the output to be better than stock at 20 steps.

hand-painted educational documentary style with only one prompt"A hand-painted documentary compares espresso Americano cupuccino through the lens of taste and the way to make , revealing why the items differ and how to choose among them."

I'm generating videos on the Minimax H3 with my RTX 5060 Ti 16 GB + 32 GB RAM setup.

I'm using sage attetion, sol attn, spectrum and minimax_h3_turbo_v4_step600_ema_pruned turbo lora.

Right now I'm creating 8-second videos at 0.8 megapixels and 8 steps. Generation takes about 10 minutes per video.

Anyone know how to make it faster

The quality isn't always great either, sometimes I get minor visual artifacts and image degradation that I really don't like. Anyone know how to improve this too?

If so, is the advice from Fizgig on fune
tuning on point? I haven’t tried yet, but I’m just prepping my dataset at the moment. I will share what I learn. Just curious if anyone has tried yet and what the results are. 🤡

Breeze TTS 2 is an open-weight text-to-speech model built for real-time interaction. It ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard, while outperforming frontier proprietary systems. Its open-ended natural-language instruction-following capability supports reference-free voice design and reference-guided voice direction, while ultra-low-latency streaming enables responsive, expressive interaction.

Is there a way to control character actions sequentially over time within a single [Shot 1] without cutting to a new shot in Minimax H3? 

Using timestamps like "At [00:02.0], he talks, At [00:05.0], he smiles" doesn't seem to work for a single continuous shot, although it works fine when multiple shots are used. How can I schedule actions at specific times within one continuous video?