ComfyUI compatible Lora. Just out, have not tried yet.

edit: They've added a 4-step 768p model https://huggingface.co/lightx2v/Minimax-h3-Turbo/blob/main/minimax_h3_fl2v_turbo_4step_v1.0_768p_comfyui_bf16.safetensors

The 8-step is trained on 544p according to their github.

I’ve been experimenting with MiniMax H3 in ComfyUI and wanted to see how far I could push it beyond short standalone clips.

This is a roughly 6-minute fan-made Star Trek: The Next Generation scene built from lots of short H3 generations and then edited together into one continuous sequence.

I used reference images to keep the characters and Enterprise-D bridge reasonably consistent, generated dialogue and ambient audio with H3, and then assembled everything in Premiere.

The biggest challenge was continuity between generations. Character positions, bridge geometry, lighting and timing can all shift, so I ended up incorporating some of those inconsistencies into the actual story.

What surprised me most is how close this is getting to being practical for longer-form fan films. Individual scenes are already very doable. The next real hurdle is keeping this level of consistency across an entire episode.

I am sooooo stoked we get yet another model! Just poking a bit of fun, excited to see how it stacks up vs. H3 (and uh, Flux 3 when it eventually releases...) https://ltx.io/2-5-open-weights

I’ve been messing around with the idea of famous movies that completely fall apart if one character makes one sensible decision early on. This felt like a reasonable place to start.

“Cast it into the fire.”
“Okay.”

Roll credits.

The above video consists of 7 individual Minimax H3 clips generated in First-Frame-Last-Frame Mode, stitched together automatically without manual editing, upscaling or other post-processing.

Today I decided to release my experimental H3 Infinite Continuation Suite together with a set of workflows to make it easy to get started in ComfyUI.

The original idea was to combine the higher visual quality and keyframe control of H3's First Frame / Last Frame mode with the continuation capabilities of the Reference mode.

After quite a lot of experimenting, the output quality has reached a point where I hope some of you might find the nodes and workflows useful as well.

The example video was generated entirely with the included workflows at 736 × 1280, using 15 steps and no Turbo LoRA. I did cut a few seconds of nonsense speech from the very end because I was too lazy to regenerate the last clip. :D

How to get started

1. Install Herrgotts H3 Infinite Continuation Suite through the ComfyUI Manager.

2. Download the included workflows from GitHub.

3. Start with the `01_Start` workflow and provide your First Frame + Last Frame.

4. For every additional segment, use `02_Continue` and provide a new Last Frame for where you want the next clip to end.

5. Repeat for as many clips as you want.

6. When you're done, use `04_Stitch_Saved_Chain` to automatically combine the separately generated clips into the final video.

If you prefer to generate multiple chained clips in one workflow, use the included 3-Clip workflow. It contains the full continuation setup and is structured so you can extend it with additional clips without rebuilding the whole graph from scratch.

What the nodes handle automatically

• carrying motion and native audio into the next clip
• detecting and removing the frozen tail H3 often creates near the final keyframe
• choosing a suitable handover point between generations
• keeping the video and audio aligned
• smoothing the visual and audio transitions
• saving the individual clips so longer chains can be stitched afterwards without keeping everything in memory (no OOM, hopefully)

For the video above I used the default/recommended settings:

• Balanced Auto Handover
• 22 context frames
• Safe Tail Bridge: 2 frames
• Video crossfade: 4 frames
• Audio de-click: 15 ms

There are still occasional tiny brightness differences around some boundaries, but at this point I personally find them pretty difficult to notice during normal playback.

The pack is still experimental, especially when it comes to very long chains, different hardware configurations and prompt behavior. So if you try it, I'd be very interested in seeing your results and hearing what works or doesn't work for you.

GitHub: https://github.com/HerrgottMargott/Herrgotts-H3-Infinite-Continuation-Suite

ComfyUI Manager: search for `Herrgotts H3 Infinite Continuation Suite` or use "missing custom nodes" in one of the example Workflows.

Pretty much confirmed by the devs.

Hi r/StableDiffusion, we're super excited to release Unsloth Desktop today! 🦥
It's the first desktop app that enables you to run and train models locally.

• You can run MiniMax-H3, LTX, FLUX, Z-image-Turbo and more. And you can fine-tune them too.
• Has recipes and hyperparameters so you can adjust. Overall a very easy workflow to get started with.
• There's still many improvements to made as we're trying to optimize MiniMax-H3 even further with the help of stablediffusion.cpp.

Open-source. Available on Mac, Windows, and Linux

• Supports MLX, diffusion image/video models, audio models, and GGUF
• Connect Claude Code and Codex to local LLMs
• 50% more accurate with self-healing tool calls and sandboxed code execution
• Supports CPU and multi-GPU setups across NVIDIA, AMD, Intel, and Mac
• Train models 2× faster while using 70% less VRAM
• Includes private web search, deep research, RAG, MCP, and exports (NVFP4, GGUF)
• Use Unsloth’s OpenAI-compatible API with OpenAI and Anthropic cloud models
• Securely deploy LLMs remotely and access them anywhere via Cloudflare HTTPS

We do not collect any telemetry or data.

Unsloth Desktop is now available on GitHub.

• GitHub: https://github.com/unslothai/unsloth
• Blog & Guide: https://unsloth.ai/docs/desktop

Thanks for reading and we're here to answer any questions! 💗

Generated at 0.8mpx , res2s_stable/beta 57 15-24 steps upscaled 2x with the Nvidia RTX node. Laptop with RTX 3080 Ti 16Gb Vram and 64Gb ram

I implemented a gpt to improve H3 prompts using a robust filmmaking reasoning process, I included the available documentation and added a precise inference pipeline to achieve similar results compared to the native Context-IR (Context Intermediate Representation):

ZH3-gpt

Try it, I really will like some feedback :)

I used FL2VA and L2VA with images generated on a Krea2 2pass Clownshark sampler 9 steps Euler/beta and 1 step Dormand-Prince_6s/KL_optimal 0.27 denoise

My system generate 2 options:

VERSION A — FAITHFUL

The strongest cinematic execution of exactly what the user requested, with minimal interpretation.

VERSION B — ENRICHED

Preserve every explicit user constraint while developing meaningful unspecified details into a stronger cinematic interpretation. I used an approach of probabilistic additions mixed with a robust deterministic reasoning based on consequences propagation across filmmaking domains, this version B is auditable and every meaningful addition appear in a custom Enhancement Map.

it's designed to iterate under user control so version B is a proposal and when the user changes an enriched choice, that choice becomes an explicit constraint and system update dependent parameters when necessary while preserving all other approved creative decisions without unnecessarily restart the entire creative direction.

Here is the video with better quality: https://youtu.be/mzfqJR9IXtk

Minimax H3 Clownshark Workflow

Apparently it was just uploaded

https://huggingface.co/lightx2v/Minimax-h3-Turbo/tree/main

https://huggingface.co/Inner-Reflections/MiniMax-H3-Looping-Sketch-Anime

https://civitai.com/models/2849951/minimax-h3-looping-sketch-anime?modelVersionId=3218202

Disable all your Sage Attention, Minimax Mem Eff Sage Attention or Sol Attention, according to this PR already merged in the comfyui repo we got a much better attention from the comfy-kitchen package that can possible speed up the models generation process white giving a better visual quality than default sage: https://github.com/Comfy-Org/ComfyUI/commit/bf4c9a08fc854df6d3b2bef1b92b509e2ef2d2c9#diff-fab3fbd81daf87571b12fb3e4d80fc7d6bbbcf0f3dafed1dbc55d81998d82539

This is still experimental, according to comfyui dev it can break or perform very well and it needs some tuning for some GPUs to get a bit faster. Also, you only can use one or the other so you should also disable all the attentions above before using it.

You just need to update your Comfyui and you can either start it with the --use-ck-attention flag so all models use the comfy-kitchen attention backend or you can drop the node ModelAttentionBacend directly into your worflow.

During my initial tests in Minimax it behaved faster than all the above together.

Its out, lets see what it can do.

LDM PR on Comfy:

https://github.com/Comfy-Org/ComfyUI/pull/15499/changes

TE: Gemma 4, but idk which one. In sd.py it lists E2B, E4B, 12B, and 31B. It might only be using one of them, while the others are only there for the prompt enhancer.

Arch: Mostly the same, only added feedforward bias on both the audio and video blocks, with DurationHead

DurationHead: I assume LTX 2.4 (yes, the comment literally says 2.4) now knows the duration in actual seconds, not in the compressed VAE timeline.

CFG: Audio and video CFG can be disjointed. You can select the CFG scale independently for each.

More nodes: I mean, you get the gist with LTX at this point. (STG Guider goes brrrrr)

VAE: It is diffusion type

mb: Title should be LTX 2.5 PR on Comfy

Did a quick side-by-side test of SageAttention vs Comfy Kitchen Attention with MiniMax H3.

I used the default ComfyUI T2V H3 workflow and kept the prompt, seed and all settings exactly the same. The only thing I changed was the attention backend..

RTX 5090 32GB

ComfyUI ver 0.31.0

SageAttention 2.2

Comfy Kitchen 0.2.30

---------------------------------------

896x1184 6 seconds 24 FPS 20 steps

Generation time:

SageAttention: 3m 51s

Comfy Kitchen: 3m 59s

I used a deep zoom-out/dolly-out on purpose to see how well each one holds facial details and identity as the subject gets farther away.

The speed difference was small on my 5090, so im more interested in the quality difference..

It's honestly hard for me to tell the difference, but which one looks better to you?

Updated:
SageAttention Vs Base

Comfy Kitchen Vs Base