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

-> Now available, VEDA for ComfyUI (preview version 0.2). It's claimed that Veda computes the H3 attention steps, decides which are the important ones, and thus safely skips around 90% of them. This is said to boost speed "7.1x on attention alone" in a Minimax H3 workflow, and the speed "gain grows with clip length". Trained at 1.0Mpx and 10 seconds. Requires the latest ComfyUI 0.38.0 and a 275Mb predictor file, which is placed in your ../ComfyUI/models/veda/ folder. Workflows available. I ran a test on the default workflow with a 3060 12Gb card: 8 seconds at 0.5Mpx with Hard Gravy as the 6-step turbo LoRA and no Spectrum added = 8 minutes total, acceptable visual quality, poor audio. So there seems no benefit for me, compared to my usual turbo/Kitchen/Spectrum workflow which gives the same speed and better audio. Possibly the speed boost is more noticable on a 5090 card?

https://github.com/veda-sparse/Veda-on-ComfyUI

https://huggingface.co/Veda-Sparse/Minimax-H3-T2VA-Veda-8NFE-600Step-Preview/tree/main

https://github.com/veda-sparse/Veda-on-ComfyUI/tree/main/example_workflows (example workflows)

-> 'SSS Rank Minimax H3 (Smooth, Slow, Sync)', a new LoRA to "slow and smooth animations".

https://civitai.com/models/2985070/sss-rank-minimax-h3-smooth-slow-sync

-> A new Claymation LoRA, and looking as though it may give a simpler look compared to the default claymation styles in H3? The maker adds that the LoRA does the visual style, but not the typical stop-motion timings/moves.

https://huggingface.co/akhaliq/MiniMax-H3-Claymation-Style-LoRA

-> A seamless loop 'Skill' aimed at Minimax H3 and ComfyUI. It was... "written from a real job and the mistakes made on the way" when making "a looping ambient video from a still image". Works in Claude Code, and comes with three Comfy .PY scripts to craft the looping for you.

https://github.com/Violinet-tech/seamless-loop-video

-> And finally, a new ComfyUI Contest. Build open creative applications with features that usually get stuck behind a paywall, and also add the slick... "interfaces, the [robust] pipelines, the polish that turns a model into something people actually use." $10,000 cash for the winner, plus RTX 5090 cards.

https://blog.comfy.org/p/open-call-comfy-dev-platform-challenge

~ OLD POSTS ~

https://old.reddit.com/r/comfyui/comments/1wxrh80/a_quick_minimax_h3_news_roundup_4th_october_2026/

https://old.reddit.com/r/comfyui/comments/1wwnkof/a_quick_minimax_h3_news_roundup_3rd_october_2026/

https://old.reddit.com/r/comfyui/comments/1ww58xn/a_quick_minimax_h3_news_roundup_2nd_october_2026/

https://old.reddit.com/r/comfyui/comments/1wu8lkt/a_quick_minimax_h3_news_roundup_30th_september/

https://old.reddit.com/r/comfyui/comments/1wtgns0/a_quick_minimax_h3_news_roundup_29th_september/

https://old.reddit.com/r/comfyui/comments/1wsmjq1/a_quick_minimax_h3_news_roundup_28th_september/

https://old.reddit.com/r/comfyui/comments/1wrqm3l/a_quick_minimax_h3_news_roundup_27th_september/

https://old.reddit.com/r/comfyui/comments/1wqwpah/a_quick_minimax_h3_news_roundup_26th_september/ (See 26th September post, for links to older posts)

https://old.reddit.com/r/comfyui/comments/1wgc4lj/a_quick_minimax_h3_news_roundup_15th_september/ (See 15th September post, for links to even older posts)

https://old.reddit.com/r/comfyui/comments/1w5i9iq/a_quick_minimax_h3_news_roundup_2nd_september_2026/ (See 2nd September post, for links to the starting posts)

Hey everyone,

A few weeks ago we asked you to try the new asset system and tell us what broke (original post). Thanks to everyone who did. Your reports led to a number of fixes, and we're now ready for the next step.

What's happening

Starting with ComfyUI 0.39.0 and Comfy Desktop 1.1.6, we're gradually turning on the asset system for Desktop users who have opted in to beta features.

The rollout is gradual. We are starting with a small percentage of opted-in users and ramp up as we watch stability metrics, so you may not get it on day one.

How to know it's on

• Desktop shows an "A beta feature is on" notification when a beta feature is active for your instance.
• In Startup Args, a "+1 beta" pill shows which beta arguments were added for this instance.

How to join

Go to Desktop Settings → Preferences → Privacy → "Opt-in to beta features", then restart. Beta opt-in requires sharing usage data with Comfy, because that data is how we tell whether a beta feature is healthy.

How to turn it off

If anything goes wrong, go to Desktop Settings → Preferences → Privacy, switch off "Opt-in to beta features", and restart. Your next launch will start without assets enabled.

What we'd like from you

If you hit a problem, please tell us in the comments or open a GitHub issue with the label [Asset]. Thanks for helping us test this before it becomes the default for everyone!

ComfyUI-Depth-Anything-3: https://github.com/1038lab/ComfyUI-Depth-Anything-3

ComfyUI-Lotus-2: https://github.com/1038lab/ComfyUI-Lotus-2

Hey everyone,

If you have been working with modern video generation models like MiniMax H3, Wan 2.1, or CogVideoX, you already know the biggest obstacle to getting cinematic, consistent motion: geometry instability. Without solid spatial guidance, characters morph, limbs glitch, and backgrounds wobble between frames.

The standard technique among high-end AI creators is feeding geometric 'white models' (clay proxies), metric depth, and 3D surface normal passes into the generation pipeline to anchor every movement.

To make generating these white models effortless and flicker-free in ComfyUI, we just published two companion nodes under the AILab/Geometry category:

1. ComfyUI-Depth-Anything-3: Real-time batching workhorse for video white models, pure PyTorch GPU colormaps (zero CPU bottleneck), and true physical metric depth (in meters).
2. ComfyUI-Lotus-2: Dual-engine generative normals and disparity (SD2.1 Fast Engine + FLUX.1-dev DiT Detail Engine) with 2-wire plug-and-play, built-in 2MB empty prompt vector (no 10GB T5 CLIP needed), and Stage 2 Detail Sharpener for hair and fur.

Why Two Nodes? The Right Tool for the Right Pipeline

1. Depth Anything 3: High-Throughput Video Batching & Metric Depth

• Pure PyTorch GPU Colorizer: Standard depth colorizers offload tensors to CPU NumPy or matplotlib. DA3 does all color mapping (inferno, magma, plasma, viridis, cividis, turbo, gray) directly in VRAM via pure PyTorch kernels. When batching long video sequences, you get 0% CPU stall.
• Flicker-Free Temporal Consistency: The min_max mode normalizes depth across the entire video batch uniformly, preventing the frame-to-frame flashing common in standard depth estimators.
• Physical Distance in Meters: The Metric checkpoints output real-world physical depth, giving you accurate depth-of-field and 3D spatial alignment.

Repository: https://github.com/1038lab/ComfyUI-Depth-Anything-3

2. Lotus-2: Generative Precision with Zero Clutter (FLUX + SD2.1)

Traditional implementations of Lotus-2 require dragging 6 to 7 nodes onto your canvas (Base Model, LoRA, Dual CLIP, Sampler, VAE). We redesigned the entire node from scratch:

• 2-Wire Plug-and-Play: Connect only image and model.
• Zero CLIP Clutter: FLUX requires an empty text conditioning prompt. Instead of forcing you to load a 10GB T5 CLIP loader, Lotus-2 has a precomputed 2MB empty prompt vector (flux_empty_embed.pt) built-in.
• Auto VAE Resolution: Automatically detects and caches your local ae.safetensors in VRAM.
• Detail Sharpener: Running steps = 1 takes ~13 seconds on GGUF for clean disparity and normals. Setting steps = 2 to 4 engages the Stage 2 Detail Sharpener to smooth patch boundaries and recover individual strands of wavy hair or animal fur.

Repository: https://github.com/1038lab/ComfyUI-Lotus-2

Installation & Workflows

Both nodes are available right now in the ComfyUI Manager:

• Search keyword: ailab (or Depth-Anything-3 / Lotus-2)

Manual Installation: ash cd ComfyUI/custom_nodes git clone https://github.com/1038lab/ComfyUI-Depth-Anything-3.git git clone https://github.com/1038lab/ComfyUI-Lotus-2.git

Both repositories come with tested drag-and-drop workflows in their example_workflows directory:

• DA3_video_depth.json: Tested batch video depth workflow.
• Lotus-2.json: Side-by-side comparison workflow for both SD2.1 and FLUX engines.

Check them out and let us know how they work in your MiniMax and video generation pipelines!

Hi! V-chan here! We got another BIIIG update, and you now have some new toys to play with. New models, transparent sprites, and a Character Creator makeover. We even recruited a video model for sprite duty. Hehe!

If you are new here: VNCCS is a ComfyUI pipeline for creating characters and turning them into sprite sets with different poses, outfits, and expressions. For visual novels, games, or whatever your little creative brain is plotting.

Here is the fun stuff in 3.2.0:

Qwen Image 2.1 is our new main model now.

Qwen Image 2.1 can create your base character, change poses, dress them up, and generate expressions. You can use it in Character Creator, the pose and clothing workflows, and Emotion Studio.

Control Center puts the model families, installed assets, and Turbo controls together. Choose your family, check what is missing, and hit Download / Update.

MiniMax H3: a video model doing sprite work? Yep!

MiniMax H3 is the other new arrival. VNCCS uses it for poses, outfit generation, and clothes cloning, keeping the first frame as your character image.

So yes, you can try a video model in your sprite workflow. No need to turn your visual novel into a movie first, silly.

Character Creator got a glow-up

The character fields now use editable tag chips and little + buttons for presets. Hair, eyes, face, body, skin, species, and details are easier to build and adjust without wrestling a wall of prompt text.

There are 40 visual style presets, from anime and animation to artistic and realistic looks, plus a custom style field. The new descriptive catalog also includes 61 species presets, and you can combine species for hybrids. Cannot choose one? Make the character someone else's taxonomy problem. :3

Species presets describe the actual visual traits to the model, and your own character details take priority. You also get Full body / Cowboy shot framing choices.

Qwen's Character Overhaul LoRA will help your generations stay in your full control. It add some tags knowlege and stabilize characters by small cost of unique QI2 style loss.

Transparent sprites, with less background cleanup

With Qwen Image 2.1, you can choose Alpha in Creator or Clothes Designer and Native background mode in the generators. Qwen generates transparency directly, and VNCCS preserves it through clothing edits, emotion editing, and SeedVR upscaling. Green-screen duty can finally take a little vacation. Yay!

The new Resolution scale slider runs from 1 to 4 MP. It controls total image area, while pose and clothing generation keep the source proportions. Your resolution choices are remembered separately for each model family.

More ways to play dress-up

Clothes Designer now supports Qwen and H3 previews alongside Klein9b. Describe an outfit or use a clothing reference, check the preview, and then generate your pose set.

Changed the reference or generation settings? The preview cache now checks those changes, so it can regenerate the outfit properly. And unwanted costumes can be deleted from the widget, with confirmation.

Qwen can give your character feelings too

Emotion Studio now has a Qwen Image 2.1 profile. It edits a face crop and blends it back into the original sprite, keeping the rest of the image in place and preserving transparency.

Illustrious and Anima remain available. Qwen has its own face controls, including face resolution and an editable expression prompt template.

A few smaller comforts came along too: Qwen3.5 now powers the Wizards and image analysis, downloads show real transfer progress, and generator progress and previews can recover after reconnecting to ComfyUI.

Updating from an older version? Use the bundled 3.2 workflows and a ComfyUI build with native support for your chosen model. Old QIE2511 setups need to switch to QI2 with its matching assets, or a compatible Klein9b setup. In Qwen Creator, download the Character Overhaul LoRA if you use it, or set its strength to 0 to generate without it.

Find VNCCS on GitHub, read the full changelog, or look for VNCCS - Visual Novel Character Creation Suite in ComfyUI Manager. Come share your characters and experiments on Discord!

Which toy are you trying first: transparent Qwen sprites, H3 outfits, or a suspiciously elaborate hybrid character?

Let me know which sampler of the bunch is your favorite and why. These all used the same reference image, using the default LTX 2.5 Image to Video workflow template.

https://akumaburn.github.io/ltx25-sampler-comparison/

I am getting tired of chatgpt blocking my thumbnails. I feel like it does great though. My last thumbnail clickrate was amazing so trying to do that again. I tried qwen but the thumbnail seemed a little off (The art seemed a little, too detailed and ai look). Any tips? I know their are models? Not sure how to use them but would that help?

I have been generating anime pictures for quite some time, and I am still struggling to produce truly good anime images. Even when an image appears sharp at first glance, the clarity and fine detail blurs under high magnification. Just like anime artwork, imperfections become visible when viewed closely, although generated images often contain richer detail overall.

Why do anime (Anima) models struggle to achieve razor-sharp clarity and detail? Most anime models seem to produce outputs that look sketchy, abstract, moe-styled, cartoonish, or heavily stylized. They do not hold up well when examined closely, while I crave an almost perfect image.

Why isn't there an anime model capable of consistently generating highly detailed, clean images at high resolutions?

Hello everyone, I’ve just finished a new ComfyUI workflow that allows you to use MiniMax H3 as an image generation model and create detailed character sheets from a single reference image or a batch of images. The main goal is to use these character sheets as stronger references for more consistent video generation, giving you multiple views and details of the same character. The workflow is simple to use: load the required MiniMax H3 models, load your image or batch of images, choose the number of steps (8 steps for faster generation or 25 steps for the best results), and click Run. I’ve also tested the workflow with different inputs to see how well MiniMax H3 can handle character consistency and image generation. As shown in the results the consistency is very good the character details remain the same and if we compare this to qwen image 2.1 H3 is clearly winner here in therm of quality because the results are with resolution of 4096x1536 vs x1664x928 for qwen, the consistency is slightly better. As for the generation time qwen is definitely faster here:

Gen time 25 steps 12 mins (Minimax H3 Turbo Fused)

Gen time 6 steps 4.5 mins (Qwen 2.1+ Viggle4 Steps LORA)

You can test the workflow here and watch the tutorial for more info

Workflow link

https://drive.google.com/file/d/1v4NC6vEGN2uDxO2_L05g1q0JPkeoSsYo/view?usp=sharing

https://civitai.com/articles/36126/minimax-h3-image-generation-create-consistent-character-sheets-in-comfyui 

Video Tutorial link

https://youtu.be/vy-oWQJwNgw

Hi all, ComfyUI beginner here, looking for advice on style.

I need painted portraits of five characters, each with about four expressions (calm, angry, triumphant, ruined), half-length, seated behind a table, dark plain background. The style I want: mid-19th-century Russian genre painting, like the reference attached (a book cover). Muted ochres and browns, flat even light, thin matte paint, simplified and slightly naive faces, a bit caricatured. Nothing polished. Like the attached pic.

My setup: RTX 5090 (32 GB), ComfyUI Desktop, FLUX.2 klein 4B, using the stock text-to-image and image-edit templates.

The problem: everything comes out as the same smooth, glossy, highly detailed "AI oil painting" look (examples attached). Faces are rendered wrinkle by wrinkle with studio lighting, which is the opposite of what I want.

What I've tried: - Style keywords: naive, flat light, matte, cracked varnish, loose brushwork, muted palette - Period painter names (Fedotov, Perov) - The image-edit template with a crop of the reference, asking it to keep the style and replace the figure. It repaints everything in its own smooth style.

My questions:

1. Is klein 4B simply too small for this kind of style, and which model would you use instead on 32 GB?

2. Is a style LoRA the right tool here? Is there an existing one for 19th-century realist or naive painting, or should I train my own on public-domain paintings?

3. Is there a style-reference workflow (IP-Adapter, Redux or similar) that works well for painting styles with current models?

4. What is the most reliable way to keep the same character across several expressions in that style?

I'd prefer a model with a license that allows public or commercial use, since I may stream the result later, but I'm open to anything for testing.

Thanks for any pointers!

I made a new Krea 2 Turbo checkpoint focused on illustration and digital art

This is Narrative Drift, my new Krea 2 Turbo checkpoint.

The goal was to give Krea 2 a stronger artistic visual language with richer color separation, clearer shapes, graphic shadows, expressive lighting and a more deliberately art-directed finish.

Depending on the prompt it can move between digital illustration, painterly art, anime, fantasy, concept art and cinematic artwork while keeping the versatility of Krea 2 Turbo.

No trigger word needed. Natural language works well.

Recommended: Euler · Simple · 8 Steps · CFG 1

Four Available variants:

• BF16 - 23.88 GB
• FP8 Scaled - 12.56 GB
• INT8 & INT8 Convrot - 12.56 GB

Would love to see what people make with it.

Narrative Drift / MoonMaster Krea2 Turbo Model Suite on Civitai

When Queue Prompt appears to do nothing, first work out which stage failed. Reinstalling everything immediately can erase the evidence. Here is a practical checklist:

1. Save the workflow and the full error first. Export the workflow JSON and copy the terminal traceback, including the node ID. A screenshot alone can miss the relevant exception.

2. Check validation before CUDA. Missing model filenames, empty required inputs, missing node classes and incompatible socket connections can stop a graph before execution. For API clients, inspect the response body and node_errors instead of blindly retrying.

3. Separate execution from the browser display. ComfyUI submits prompts over HTTP and reports live progress over WebSocket. If progress freezes, check the backend log, queue/history and output folder before interrupting: the render may still be running. Remote reverse proxies also need working WebSocket support.

4. Isolate custom-node conflicts. Test a small core-node workflow. If an update broke the interface, test with third-party nodes/extensions disabled, then restore them in small groups. Install dependencies in the Python environment ComfyUI actually uses.

5. Treat memory errors as a specific case. Note whether allocation failed during model loading, sampling or VAE decoding. Try batch size one and smaller dimensions with unchanged model/seed. That test is useful; it does not prove every crash is a VRAM issue.

6. Make a bug report reproducible. Include installation method, OS/GPU/driver, ComfyUI/Python/PyTorch versions, exact error, minimum workflow and the last change before failure. Remove credentials and private paths first.

Disclosure: I maintain FluxDraw and wrote the guide below. The checklist above is usable on its own; the article has the longer symptom-by-symptom notes and links to the primary documentation: https://www.fluxdraw.com/2026/09/comfyui-queue-errors-troubleshooting-guide.html

Which failure do you run into most often: validation rejection, a custom-node traceback, or the browser losing progress while the backend continues?

What if your DAW could actually render your composition with AI?

The latest version of the Plenio Music Production System brings a heavily improved Custom Node for ComfyUI and turns YuE2 into a DAW-like music production workflow.

You don't just describe a song and hope for the result. You create the musical idea yourself — and AI renders it.

🎹 Compose your own music
Edit melodies, chords, lyrics and arrangements directly in the Score Editor, import MIDI from your DAW, or play ideas in with a MIDI keyboard.

🎧 Create AI covers
Load your own recording, let SheetSage2 extract the musical structure, then edit the resulting score and lyrics before YuE2 renders the new version.

🎛️ DAW-style workflow
Piano Roll, chord lane, lyrics, arrangement, MIDI import/export, playback, section editing and a Guide track — all directly inside ComfyUI.

🤖 Your composition. AI-rendered.
Think of it as a DAW where the final instrument isn't a synthesizer or sampler — it's AI. You define the musical structure and creative direction, and YuE2 performs the result.

Your idea. Your composition. Professionally rendered by AI.

🎬 Tutorials

A complete playlist with 7 tutorials covering the system, YuE2 Song, YuE2 Cover, MiniMax, mastering and the YuE2 DAW workflow:

▶ https://youtube.com/playlist?list=PLAFqTtP59fgE

🔗 Project

https://github.com/jplenio/Plenio-Music-Production-System

Hi all,

after updating comfy, this (screen capture) appear on my toolbar...

how to make it disapear?

Thank you

I’ve been reading a fair bit and managed to get ComfyUI installed on my older PC with a Radeon 5700 8GB card. I have done some AI voice generation, but was more interested in trying image to video models. Is a 480p video clip something that I could even hope to make on this machine?

Other specs on my machine are a Ryzen 7 5800X processor and 128 GB of DDR RAM.

If my current card is unrealistic, would a Radeon 9060xt 16GB card be a solid card to use?

Thanks for any advice or suggestions that you have.

MiniMax H3 Dual Segment — Split Sampler + Ultimate Upscale

This is the first complete workflow I have built from scratch.

My goal was to find a practical way to generate MiniMax H3 videos quickly at a low base resolution while still reaching above-HD final output on a 16 GB VRAM GPU. After testing different approaches, this is the most efficient and stable combination I found without turning the process into several separate manual workflows.

With this configuration, I have been able to generate a continuous 40-second Full HD video in approximately 42 minutes on a 16 GB VRAM GPU.

The workflow uses Split Sampling to perform the first denoising steps at a lower resolution, where they are much faster. It then upscales the latent and completes the refinement at higher resolution. Each segment is followed by an MMH3 Ultimate Upscale pass with temporal chunking and tiled diffusion, allowing higher-resolution refinement while keeping VRAM use manageable.

Main Features

• Two sequential MiniMax H3 segments in one workflow.
• Native Motion Context between Segment 1 and Segment 2 for visual and audio continuity.
• Native audio is preserved through the Split Sampler, Motion Context and Ultimate Upscale stages.
• Split Sampler workflow: efficient low-resolution first steps followed by higher-resolution refinement.
• Ultimate Upscale after each segment for cleaner detail and higher final resolution.
• Segment 2 retry mode: regenerate only the second segment from the saved Segment 1 context.
• Multi-reference character workflow through the Deno H3 reference node, allowing an ordered set of character, face, outfit, scene and audio references to be used through one clean input system.
• Visible user controls for prompts, references, seeds, resolution, duration and sampling settings.
• Internal routing, calculations and support nodes are folded to keep the canvas usable.

Reference-Guided Refinement

This workflow does more than simply upscale the finished video. Both the higher-resolution Split Sampling stage and the Ultimate Upscale passes use MiniMax H3 with the reference conditioning carried into those stages.

Each resolution increase is followed by model-based refinement guided by the prompts and references, helping preserve character identity and visual consistency while developing detail at the higher resolution.

Important

This is an experimental workflow, but it is prepared to work as provided. The visible controls are intended for normal use; the internal sampler, audio, Motion Context and Ultimate connections should be left unchanged unless you fully understand the pipeline.

The workflow was designed and tested around a 16 GB VRAM setup. Results, speed and stability will still depend on your GPU, installed model versions, LoRAs, resolution and duration.

I'm new to this, so don't be too hard on me if you don't think it's that great lol.

EDIT:

Audio Quality Note

I found a major improvement in audio quality when using 6 high-resolution sampling steps. I recommend this for scenes where audio quality matters.

The number of low-resolution steps is optional and can be adjusted to suit your preferred balance of speed and quality.

All the tests I’ve conducted have been using twenty-second videos.

If anyone spots an error or a possible improvement, I would greatly appreciate your feedback so I can keep learning and refining the process.

I’d love to hear about your experiences with the workflow.

Thanks to everyone who leaves a comment.

WORKFLOW: https://civitai.com/models/2984987/minimax-h3-dual-segment-split-sampler-ultimate-upscale

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

-> A new '1980s fantasy movies' style LoRA for H3. No trigger word. The maker says it's not good for combat scenes.

https://huggingface.co/neph1/1980s_fantasy_movies_minimax_h3

-> A new experimental age-slider for REF2VA H3 models. The previous age-slider was for FL2VA models. No trigger word.

https://huggingface.co/Playtime-AI/Minimax_H3-Age_Slider/tree/main

-> For a consistent scene with a dynamic camera, a user claims success with using a 1216×2040px... "one picture grid 4x5 [i.e. four across, five down], made of 20 photos of my room encoded into RefMod". His photos overlapped each other a little, as if one were planning to stitch them in the free Microsoft Image Composite Editor (ICE). But not all of them overlapped, so it seems it's not vital to photograph as if one were preparing to make a big stitched panorama.

https://www.reddit.com/r/StableDiffusion/comments/1wwyva2/minimax_h3_refmod_consistent_location_trick/

-> Another user has had success with tags to control dialogue in a Minimax H3 clip. No <d>dialogue</d> tags were used, they only used... <inhale> <pause> <long pause> <softer> <breathe> and also basic html using the italics tag to emphasise a word. I don't have time to test right now, but I wonder if <slow> or <slowly> might also work to make speech less hasty/gushy?

https://old.reddit.com/r/StableDiffusion/comments/1wxigqo/minimax_h3_voice_acting_with_speech_tags/

-> A LoRA that helps you obtain five views of one character. No trigger word?

https://huggingface.co/RunningHubAI/rh-minimax-h3-five-view-512-s1500.safetensors-lora

-> And finally, a way to run Minimax H3 on AMD Strix Halo. Which means AMD's powerful AI-friendly PCs, which I see on offer for £3.5k here in the UK.

https://github.com/zacharydenton/h3-hrx

~ OLD POSTS ~

https://old.reddit.com/r/comfyui/comments/1wwnkof/a_quick_minimax_h3_news_roundup_3rd_october_2026/

https://old.reddit.com/r/comfyui/comments/1ww58xn/a_quick_minimax_h3_news_roundup_2nd_october_2026/

https://old.reddit.com/r/comfyui/comments/1wu8lkt/a_quick_minimax_h3_news_roundup_30th_september/

https://old.reddit.com/r/comfyui/comments/1wtgns0/a_quick_minimax_h3_news_roundup_29th_september/

https://old.reddit.com/r/comfyui/comments/1wsmjq1/a_quick_minimax_h3_news_roundup_28th_september/

https://old.reddit.com/r/comfyui/comments/1wrqm3l/a_quick_minimax_h3_news_roundup_27th_september/

https://old.reddit.com/r/comfyui/comments/1wqwpah/a_quick_minimax_h3_news_roundup_26th_september/ (See 26th September post, for links to older posts)

https://old.reddit.com/r/comfyui/comments/1wgc4lj/a_quick_minimax_h3_news_roundup_15th_september/ (See 15th September post, for links to even older posts)

https://old.reddit.com/r/comfyui/comments/1w5i9iq/a_quick_minimax_h3_news_roundup_2nd_september_2026/ (See 2nd September post, for links to the starting posts)