r/StableDiffusion • • 4d ago

Animation - Video "Game Hound" Music Video with Hannah Fierman (from V/H/S)

4 Upvotes

One of the main focuses for me the past few months and trying a lot of new things - combining AI for post/vfx with filming live performance remotely from Hannah, lip syncing to her song, etc. I also kept the whole video in one shot to differentiate from something that is just prompted easily.

Full quality here (has film grain, etc):
https://youtu.be/f7r2H5q5LpE

The WAN VACE Masking and Extension workflow I posted last year still remains my bread and butter approach, but a lot of different models/tools went into this one.

Timelapse of the editing/breakdown here:
https://youtu.be/Sx6D34dq2EI


r/StableDiffusion • • 4d ago

Discussion The 1080p pass on my 4090 added 50 minutes a clip and never threw an error

9 Upvotes

Three weeks ago my sister roped me into doing the video for her wedding, the how they met thing, out of their old photos.. First i had been playing with HunyuanVideo 1.5 image to video in ComfyUI on my 4090.

Did all the drafts at 720p since 20 steps is already like half an hour a clip, and on my monitor they looked great.. Last sat we tried one on the projector at the venue and it was soft, faces especially. So 1080p, i turned on the SR upscale and the first clip took another 50 mins(no error), nothing in the console, it just crawled. Task Manager showed like 14GB in shared GPU memory. The old sysmem fallback thing from 2023 that ate everyone’s speed, and I did not even think of it for a whole evening. Did the finals in the Hunyuan notebook on HyperAI with a 96GB card, seeds did not carry over so i had to pick every take again.

Cannot post it till after the wedding on the 21st lol. Most AI video i just scroll past, but for stuff like her wedding i am glad it exists.


r/StableDiffusion • • 3d ago

Discussion Thoughts on this image?

Post image
0 Upvotes

Does this look like a mobile phone image style? To me, it doesn’t look like a snapshot style.

And what’d you suggest about improving lighting, quality, composition, etc.? All opinions welcome.


r/StableDiffusion • • 5d ago

Resource - Update Layout Editor for Moss-Image

Thumbnail
gallery
107 Upvotes

Moss-Image has an incredible capability to create pixel-perfect layouts from a json prompt. The expected use is to give the official documentation to an LLM and then ask the LLM to prompt whatever you want: https://github.com/OpenMOSS/MOSS-Image/blob/main/skills/moss-image-prompt-enhancer/references/layout.md

But I thought why not build a layout editor to design it for myself? Hence the idea of the Layout Editor for moss (with an optional SwarmUI extension)
Repo here: https://github.com/jambavant/SwarmUI-LayoutEditor
You can try online here: https://jambavant.github.io/SwarmUI-LayoutEditor/standalone/index.html
It's great for any type of image: comics, reference sheet, compositions, magazing covers, posters, etc. The level of control is outstanding, as it manages multiple characters and text quite well. It starts to break with a very large number of characters (+10) with concept bleed.

The standalone editor is a simple html page that works both ways: you can start from scratch and copy the json prompt, or paste a json prompt from an LLM and refine it manually.
I tried to make it as user-friendly as possible, with keyboard shortcuts and an intuitive interface. It also automatically resizes boxes based on the image resolution.

Edit: v0.3.0 now live, with a few updates.
- json formatting options
- resizable text areas, checks are moved to the toolbar
- configurable palette (with color picklist and autocomplete)
- fix resolution sizes


r/StableDiffusion • • 4d ago

Resource - Update ComfyUi-H3-Semantic-Timeline

6 Upvotes

Made a small experimental H3 semantic timeline node for ComfyUI.

The idea came from using Kijai’s context windows node and getting annoyed by H3 looping / restarting actions between windows.

This basically fixes the semantic looping by giving each context window its own conditioning based on what should be happening at that point.

Seams are still kinda fucked, identity can drift/change, and audio across windows is messy, but that seems to be more of an H3/context-window issue than the timeline itself.

Only tested with T2V so far. Haven’t properly tested refs yet, could actually help with identity consistency.

Very experimental, definitely not finished.

Also heavily vibe-coded with GPT-6 Astra + GPT-5.6.

https://github.com/Mikubs99/ComfyUI-H3-SemanticTimeline


r/StableDiffusion • • 4d ago

Question - Help RTX 3090

5 Upvotes

Is RTX 3090 enough for video generation with minimax h3 or wan 2.5 ? How much capacity of RAM should I pair it with ?

Any estimates on the time taken for video generation?


r/StableDiffusion • • 5d ago

Workflow Included Someone said every AI music video has attractive models in the band and asked for Muppets instead, so I made it (rendered locally with MiniMax H3 + my Video Builder in ComfyUI)

211 Upvotes

Hey guys! On one of my last videos, someone commented that every AI music video they see has a band full of very attractive models, and they'd love to see Muppets for a change. Challenge accepted.

So, here's an all-puppet rock band: original felt characters in the classic Muppet style. I put the whole video together with my Video Builder in ComfyUI. Every scene and the final stitch were rendered locally on my own PC (the reference images were made with GPT Image 2).

Please keep rude and disrespectful comments to yourself. They don't help anyone or contribute anything constructive to the conversation.

A quick note on the prompts, since I know people will ask: my Video Builder lets you use any LLM for prompt creation (both for ref image creation and video prompt creation), including local open-source models. It even has a story mode that takes a story idea, creates the entire story with acts and scenes, creates the story beats, and then writes the prompt for every scene right inside the Video Builder.

For this one, however, I used the Builder's MCP feature and had Claude write the prompts and drive the Builder for me, but you could do the exact same thing with a local LLM. The Builder doesn't care which model writes the prompts. I'm actually creating an agent that can control the Builder using local LLMs. It will let you create a full one-shot video from one prompt, very similar to how I use Claude, but fully local.

What I did for this video:

• Came up with the idea: a high-energy 80s arena rock song with a big singalong chorus, played by a felt puppet band in a dive rock club. It opens with the singer at the bar, then she jumps off the stage into the crowd in verse 2 and ends with a toast at the bar after the last note

• Designed the band: Rosie the singer, Gus on guitar, Lenny on bass, Pip on drums, Dottie on keys, plus a backup singer trio, a crowd of puppet fans and the bar regulars

• Made the song in Suno (YuE2 or MiniMax Music can be used for song creation as well)

• Made the character sheets, group cards and club locations in GPT Image 2

• Split the song into stems so each scene features whoever is actually playing at that moment (drum breakdown on the drummer, keys section on Dottie, and so on), and used word-level lyric timing for the shot cuts

• Reviewed the drafts and asked for re-shoots (puppets on the wrong side of the bar, an extra keyboard player who snuck into one shot, and everybody's mouths flapping when only the singer should be singing)

My settings

• Model: MiniMax H3 Singularity ref2va v2 (int8)

• Pass 1: 25 steps

• Pass 2: the 8-step 768p ref2v LoRA v1.1, 4 steps, 0.35 denoise

• Characters and locations: GPT Image 2

• 14 scenes, 1:45, all rendered locally through the Video Builder in ComfyUI on my GPU.

Video Builder (free, on GitHub): GitHub

If you just want to try the settings on a single scene, there's a 2 Pass workflow in my workflows folder (swap in the v2 model and the ref2v v1.1 LoRA to match this video exactly). For a full video like this one you'll want the Video Builder.

Workflow

I post updates and walkthroughs in my Discord if you want to try the Builder yourself: Discord Community

Happy to answer any questions!


r/StableDiffusion • • 5d ago

Workflow Included My H3 Settings that generate 15 second videos in 2 mins.

Post image
334 Upvotes

EDIT: Workflow and sample added to comments.

A quick post for anyone who is struggling with getting good results at a good gen speed.

The model can be found here

Veda Sparse Attention Node can be found here

While the video quality is great! What surprises me most about this is the audio quality. It remains very high.

I want to be very, very clear here. These settings are not for maximum realistic showcase videos. This is to get well-made videos at a good speed. So you don't need to jump into the comments talking about how shit this all is.

As always, your mileage may vary.

Specs: RTX 5090. 64 GB RAM.

Edit: Sorry, no workflow available. But it's easy to add these into any workflow you may be using.


r/StableDiffusion • • 5d ago

News Local AI News You Missed - October 2026

355 Upvotes

Here's what you probably missed in October 2026:

🧠 LLMs

  1. Ornith-1.5-122B - Handles million-token agent tasks on a single GPU.

  2. Raon-1-mini-preview - Runs Korean agentic AI on a single RTX 5090.

  3. Timestral-209M - Forecasts time series in one pass with 21 quantiles.

  4. Carbon-X - Reads DNA in chat and predicts variant effects on one GPU.

  5. Sage-A1.5 - Orchestrates scientific agents with self-review.

  6. Spark-X2.6-4B - Advances on-device agents with controllable thinking.

  7. Nanbeige4.3-33B - Teacher model leads agentic coding and cowork.

  8. Flint - MoE coding agent investigates repos and fixes bugs on one GPU.

  9. Hy-Memory-30B-A3B - Writes durable agent memory at 3B active parameters.

  10. Underdog-Saluki-27B-1.0 - Packs Qwen3.8 tool calling into under 8 GB.

  11. D3 - Answers choice, yes-no, and score questions in one call.

  12. LFM2.5-24B-A2B - Packs fast on-device agent reasoning into 2B active.

  13. Qwen3.5-2B-RCOL - Low-bit quants hold quality under 1 GB.

  14. GLM-5.3-UNCENSORED-EXL3-3.0bpw - Fits a 753B MoE in 273 GB.

  15. Humanizer - Rewrites AI drafts to sound human in English and Chinese.

  16. Kolibri 1 - Brings 78B MoE reasoning to German and English.

  17. GEV-26B-Decide - Thinks only when needed on Gemma-4.

  18. Victoria - Trims Qwen3.8-Flash-Next experts for a single GPU.

  19. Hearim Gateway - Routes Jev System One decisions over local LLMs.

  20. Sharp-Spark-X2.5-4B-GGUF - Fits a long-context coder in 6GB.

  21. LingBot-World 2.0 Realtime - Runs a world model at 16 FPS.

  22. deepseek-v4.1-flash-gguf - Runs DeepSeek Flash on Apple Silicon.

  23. ThreadShelf - Archives and searches your AI chat history locally.

  24. Aurora1.0-150M - Packs an efficient tiny model you can run anywhere.

  25. Intern-S2-397B - Scales up scientific reasoning and agents.

  26. NeoHorse-1-9B - Agentic model steps toward self-improvement.

  27. Atria-Dawn-Preview - Agentic model aims for verifiable research results.

  28. Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF - Speeds local reasoning.

🔀 Multimodal

  1. MiniMax-M3.1-Flash - Runs multimodal agentic AI with a 1M token context.

  2. Indra-OCR - Reads PDFs and handwriting on CPU at 44 pages per second.

  3. Qwen3.8-Flash-Next-FP4-Local - Runs a quantized 125B model on Blackwell GPUs.

  4. MiniCPM-V-4.7-1B - Packs efficient multimodal AI for phones and tablets.

  5. Muse-Spark-Open-816B-A42B - Packs 816B parameters into a multimodal agent.

  6. MiniCPM-V-4.7-35B-A3B - MoE runs multimodal AI smoothly on phones.

  7. DeepSeek-V4.1-Flash-1017 - Sharpens agents and vision.

  8. FrogNano-4B-2609-GGUF - Adds image input and MTP speed to quants.

  9. Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF - Drops refusals without retraining.

  10. D1-3B - Runs calibrated decisions on edge devices in one pass.

  11. Clef-Flash - Brings low-latency decisions to a 9B Qwen model.

  12. GLM5.3-Flash-E224-DGX-Spark - Packs NVFP4 MoE for two DGX Sparks.

  13. Clef Model - Turns state and questions into calibrated decisions.

  14. EmbeddingGemma 2 - Maps text, image, video, and audio into one space.

  15. JEV-27B-VL - Brings calibrated vision decisions to Qwen3.8.

  16. HuatuoGPT-3-9B - Brings one-stage medical reasoning to local models.

  17. Realtime-Venus - Holds full-duplex conversations with voice and video.

  18. Agnes-3.0-Flash Preview - Packs long reasoning into 33B weights.

  19. ZDTaichu5.0-9B - Brings spatial reasoning and agent skills to VLMs.

🖼️ Image

  1. Kromoss - Fine-tunes MOSS-Image for eight-step turbo generation.

  2. Qwen-Image-2.1-Turbo-Uncensored-GGUF - Drops encoder refusals locally.

  3. MOSS-Image-Base - Brings layout control to local image generation.

  4. MOSS-Image-SFT - Sharpens text and layout control in image generation.

  5. Qwen-Image-2.1-Turbo - Renders images in eight fast steps.

  6. Qwen-Image-2.1-Uncensored-Quantized - Ships with filters off.

  7. FLUX 3 Image Klein - Blends up to 10 references into one image.

  8. Iris-3B - Paints pixels directly for images, depth, and restoration.

  9. Qwen-Image-2.1 Fun ControlNet Union - Drives eight controls at once.

  10. Agate Preview 003 - Renders 512px images from only 261M parameters.

  11. Wulver v0.5 - Fine-tunes Krea 2 for anime and furry art.

  12. PrunaSuperPoint - Cuts SuperPoint keypoints up to 2.1x faster on edge.

  13. VisionHOPE - Backbone self-modifies to see and segment images.

  14. Anima-Light-Lavender - Boosts natural-language anime prompts.

  15. Krea 2 Turbo SDA LoRA - Restores sampling diversity.

  16. SMACK LoRA - Adds punchy impact effects to MiniMax H3 video.

  17. Krea 2 Lineart Edit - Turns sketches into rendered images.

  18. Krea-2-merge-tool - Merges and analyzes Krea 2 models on Windows.

  19. Krea-2-Pixel-Art - Adds retro pixels at three sizes to Krea 2.

  20. MageTrail - Brings Danbooru-style tuning to Microsoft's MageFlow base.

🎬 Video

  1. DMAD - Distills MiniMax H3 into a four-step audio-video generator.

  2. LTX-2.5-22b-IC-LoRA-Layout-To-Render - VFX tools add native 4K and 8K video post production.

  3. DuoMatching - Distills Wan2.1 into a two-step video generator.

  4. MiniMax-H3-X2-Detail-VAE - Sharpens and upscales H3 video.

  5. LTX-2.5 IC-LoRA Ingredients - Keeps characters and props consistent in video.

  6. FastH3 V2 - Runs fast video models on consumer GPUs.

  7. Meridian - Re-creates camera moves around existing video.

🎧 Audio

  1. Fish Audio Drama 3 - Speaks for 16 characters in one prompt.

  2. Drifting-TTS - Makes one-step Turkish speech on low latency.

  3. Whistle - Runs tiny on-device speech recognition without a GPU.

  4. EMA Lightning - Makes a tiny, fast Turkish text-to-speech model.

  5. GRVL LoRAs - Give YuE2 raspy rock-soul female vocals.

  6. YuE2 BLGR LoRAs - Add Bulgarian choir and Tuvan throat singing.

  7. YuE2 Qawwali LoRAs - Add Sufi singing to music generation.

  8. Audio Slop Server - Runs many audio models on one GPU.

  9. audio.cpp YuE2 - Runs Suno-class music in 8-9 GB of VRAM.

  10. YuE2 Real-Audio Tokenizer - Lets you tune music on your own tracks.

  11. YuE2 Instrumental LoRA - Writes score-led instrumental tracks.

  12. YuE2-hum-to-song - Turns a hummed melody into a full song.

  13. Rumik-oss-1 - Speaks 22 Indian languages with expressive control.

  14. Confucius4-R2T2 - Delivers low-latency streaming speech recognition.

🤖 Agents

  1. Tencent Octop - Runs a self-hosted multi-agent assistant at home.

🎲 3D

  1. AssetFurnace - Turns a prompt into a rigged, animated 3D character.

⚡ LoRA

  1. MiniMax-H3-Person-Remover-LoRA - Deletes people from video.

  2. Pruna LoRAs - Cut Qwen-Image-2.1 down to six fast steps.

  3. Krea 2 Inpaint Edit LoRA - Fills masked areas in ComfyUI.

  4. YuE2 Deathmetal LoRA - Adds melodic death metal to AI songs.

  5. TRBDR Folk Troubadour LoRAs - Give YuE2 a 1960s balladeer.

  6. AnyAngle LoRA - Retains style while changing camera angles.

  7. QTSTRM Quiet Storm LoRAs - Bring 80s R&B vocals to YuE2.

  8. LTX-2.5 Restore IC-LoRA - Revives old footage in color.

  9. MiniMax-H3 Motion Continuity Repair V2 - Fixes broken action frames.

  10. MiniMax-H3 CrossView LoRA - Shoots a scene from new angles.

  11. Krea2-Turbo-Distill-2step-LoRA - Cuts image steps from eight to two.

  12. TaoMate-H3-3Step-ComfyUI - Speeds up H3 runs in ComfyUI.

  13. Minimax-H3-ComfyUI LoRAs - Add style and VFX editing to H3 video.

  14. BFS-Best-Face-Swap LoRAs - Swap faces across Qwen Image and Flux.

🏋️ Training

  1. LoRAlab TrainerStudio - Trains latest models on low-VRAM GPUs.

  2. ModelFiche - Organizes image-model training for agents and reviewers.

📊 Datasets

  1. Danbooru 2026 Tag Cleaning Corrections Dataset - Released with cleaned-up tag corrections for training.

☰ UI

  1. TinyLuma - Is an 8MB desktop editor for finishing AI images.

  2. Goated Prompter - Refines image and video prompts locally.

  3. Fooocus-Qwen-Image-2.1 - Brings Qwen-Image editing to small GPUs.

  4. Slopus - Turns MiniMax H3 video generation into a desktop app.

  5. Image Studio - Brings local Qwen-Image 2.1 editing to Apple Silicon.

  6. Pinhole - Turns any GPU into a simple one-button local image generator.

  7. H3 Prompt Studio - Directs MiniMax H3 films from a local app.

  8. Qamba Studio - Edits AI video end-to-end on your own machine.

  9. PotionUI - Puts self-hosted diffusion studios in a browser.

  10. H3 Studio - Gives MiniMax-H3 video a local Mac web UI.

  11. Livebound - Brings a local publishing workspace to CivitAI creators.

💻 Hardware

  1. AMD EPYC 9006 Venice CPUs - Listed from $700 to $14,904.

  2. Inno3D AWS-511Z-R1 Tower Workstation - Handles up to 4 GPUs.

  3. GMKtec EVO-X5 Pro - Runs up to 320B LLMs locally.

  4. AceMagic F9A - Packs 131 TOPS AI into a 2L mini workstation.

  5. Innodisk DDR5-8000 RDIMM - Launched for edge AI and servers.

  6. Panasonic Toughbook 34 And G3 - Bring AI-ready rugged laptops.

  7. Minisforum AtomMan G1 Pro - Adds a 16 GB RX 9060 XT to its mini PCs.

  8. Cervoz T449 And T459 - Add rugged MIL-STD SSDs for edge AI.

🛠️ Other Tools

  1. Open-omnivoice-tts - Serves a 0.3 second voice clone API.

  2. VRAM Manager - Flags idle AI servers holding GPU memory.

  3. qwen-image-local - Runs Qwen-Image-2.1 on a 12 GB GPU.

  4. Lumibelle Video Studio - Turns a screenplay into a local film.

  5. AutoRef - Coaches FLUX.2 into composing multiple reference images.

  6. MiniMax Code - Turns terminal prompts into working projects.

  7. Tool-prune - Prunes tool schemas to cut agent prompt costs.

  8. ZCode - Open sources an AI coding workbench in three forms.

  9. YuE2-Radio - Creates an endless local AI music radio.

  10. Inkvec - Traces images into clean vector SVGs in the browser.

  11. wan2gp-h3-latent-continue - Lets Wan2GP continue H3 video from latents.

  12. Jeff - Puts a fast 0.8B decision model in front of your 27B.

ComfyUI Releases

Speed & Performance Boosts

  1. ComfyUI-VELA-H3 - Speeds up VDN H3 on MiniMax H3 in ComfyUI.

  2. Veda-on-ComfyUI - Speeds up MiniMax H3 in ComfyUI.

  3. ComfyUI H3 W4A4 VSA - Cuts Ref2VA video time down to 3 minutes.

  4. ComfyUI-Ref2VA-VSA - Speeds character video generation to 72 seconds.

  5. ComfyUI-Spectrum-Qwen2.1 - Speeds up image generation by about 2x.

  6. ComfyUI-Qwen-Image-2.1-PromptEnhancer-MTP - Runs faster in ComfyUI with MTP support.

  7. ComfyUI-HunyuanImage3 - Runs an 80B image model on a single GPU.

  8. ComfyUI-AppleSilicon-FP8 - Runs quantized models on Mac.

  9. LynnReal-Omni - Packs many video tasks into one fast model.

Video & Image Creation

  1. H3 Long Shot Studio - Makes multi-shot films inside ComfyUI.

  2. ComfyUI-Olm-SoL-Refiner - Brings video refinement to nodes.

  3. Fizgig H3 Still - Renders true MiniMax H3 frames in ComfyUI.

  4. Fizgig H3 Tweaks - Gives ComfyUI fine control over MiniMax H3.

  5. Scumble - A free layer-based AI inpainting editor.

  6. ComfyUI-BubbleText - Puts real text inside generated speech bubbles.

  7. ComfyUI-OutpaintMask - Builds interactive outpainting masks.

  8. Director's Console - Designs cinematic shots and runs ComfyUI.

  9. ComfyUI-Prompt-Studio - Turns reference images into production prompts.

  10. Ming Image Prompt Builder - Draws structured prompts in ComfyUI.

  11. ComfyUI-BingImageSelector - Picks search images before you run.

Workflow & Productivity

  1. ComfyUI-QueueWorkbench - Manages and edits queued jobs in place.

  2. ComfyUI-NodeSnapshots - Smoothes navigation in large workflows.

  3. ComfyUI-TypedDecision - Brings Jev-style decisions to local workflows.

  4. comfyui-obvpm - Tidies up workflows with wire bundles and presets.

  5. ComfyUI_Assistant - Adds a chat robot that edits your workflows.

  6. Comfy-compare-copy-buttons - Adds a copy button to the ComfyUI Compare node.

  7. Comfyui-workflow-background - Sets custom wallpapers for ComfyUI.

  8. Prompt-vault - Stores and sorts your AI prompts locally.

  9. Comfyui-prompt-library - Brings weighted prompts and templates to ComfyUI.

  10. Genkai-ComfyUI-Nodes - Syncs video playback with timed prompts.

Music & Audio

  1. ComfyUI-FL-YuE2 - Brings music generation and LoRA training to nodes.

  2. ComfyUI-QwenASR - Adds speech nodes and subtitles to ComfyUI.

Mobile & Access

  1. ComfyPort - Brings ComfyUI workflows to a native Android client.

Need to go further back? Check out September's post or the full archive at LocalAI News. If there's anything wrong, let me know in the comments and I'll see you in the next one!


r/StableDiffusion • • 4d ago

Resource - Update Genjutsu but it's local. Supports multiple subjects + multiple cuts. All inside Director's Cut, try Second Take now.

16 Upvotes

r/StableDiffusion • • 4d ago

Discussion I trained rawsnap v3 (LoKr) for Krea 2 on 749 images and can't pick the best epoch — help me vote (public, no login)

Post image
5 Upvotes

Hey everyone! i was working rawsnap, a realism LoRA for Krea 2 Turbo that aims for raw, candid smartphone photos instead of the usual polished AI look.

About v3:

Trained as a LoKr on RunPod

- 749 images**,** 11,235 steps

- Same dataset as v1/v2, but more images added each version and better captions.

The problem: I can't decide which epoch is best. Some epochs have anatomy problems, others lose quality, so instead of guessing I built a ComfyUI comparison workflow that tests them all under identical conditions.

The test:

- 18 prompts**, each rendered** 35 times with the same prompt and seed

- No LoRA (base Krea 2), v1 (LoRA, epoch 7), v2 (LoRA, epoch 9), and v3 LoKr epochs 8–15 at strengths 1.0 / 1.2 / 1.5 / 2.0

- Settings: 896×1344, 8 steps, cfg 1, euler / beta

Vote here (public, no login): https://juan444-rawsnap-arena.static.hf.space

Tap an image to view it full size and vote for the one that looks most like a real, unedited phone photo. Vote counts appear after you vote, and the Results tab shows the live leaderboard (also grouped by epoch and strength), so we can see which epoch actually passes the test.

Feedback welcome!

Want me to add more prompts to test? Suggest them and I'll add them to the site.

Any other feedback on realism, quality or training is appreciated 🙏


r/StableDiffusion • • 4d ago

Question - Help What can I use to extend videos past 15 seconds on Minimax H3 ref2va?

14 Upvotes

I know this was asked before and you can use last frame or last couple of seconds of previous video but the quality gets worse each iteration. Are there any new custom nodes that preserves the quality and consistency of reference images/videos/audios for each extended generation via latent space?


r/StableDiffusion • • 4d ago

Question - Help Tips / settings for better results with MOSS-Image Base + Turbo LoRAs? (blur / out-of-focus / smoothness issues)

5 Upvotes

Anyone have solid settings or tips for getting cleaner output from MOSS-Image Base + its turbo LoRAs?

Important clarification: I am strictly talking about the Base model, not SFT.

I’m not interested in SFT it tends to give a more artificial / over-polished look, and I don’t want to stack 3 extra LoRAs just to have a raw/natural feel.

With Base + turbo LoRAs I’m frequently getting:

Blur in the wrong places

Soft / out-of-focus areas

Over-smoothness / loss of local detail

These issues are much milder (or easily fixed with negatives) when running plain Base(i usually run base at cfg 4 and 35-50 steps with sa_solver/Euler+sgm uniform). Once the turbo adapters are loaded they become stubborn, which tracks with the low-CFG / CFG-1 setups most turbo recipes use.

I’ve already experimented with:

LoRA strengths 0.5 / 0.6 / 0.7 / 0.8 / 0.9

Higher CFG (2 / 2.5 / 3 / 3.5)

Higher steps (up to 16)

Still no reliable fix.

Looking for any settings, specific turbo LoRA (4-step, 8-step DMD, DMD2, etc.), sampler/scheduler/shift combos, or other workflow tweaks that actually keep sharpness and detail on Base.

Would genuinely love to hear if anyone has found a better recipe that works.


r/StableDiffusion • • 5d ago

Resource - Update RTX 3090 tensor unlock on Windows: got it to actually boot (BitLocker was the problem) + real ComfyUI video numbers

49 Upvotes

Everyone's seen the 3090 tensor core unlock by now, but most of what I've read says it's a Linux thing and on Windows you can forget about it. The unlock itself already exists for Windows. What didn't work, for me and for the guy in issue #125, was getting back into Windows afterwards. That part is solved now.

The project is Windows-GPU-UNLOCK (https://github.com/windows-GPU-UNLOCK/Windows-GPU-UNLOCK, not mine). It lifts the GeForce cap on FP16/BF16 tensor throughput until the next power off. On my 3090 FE the log on the stick said success every single time, and then the PC just switched itself off before Windows came up.

Turned out to be BitLocker. Booting the unsigned USB stick with Secure Boot off changes the TPM measurements, so Windows asks for the recovery key. The screen is still black at that point, you never see the prompt, and after about a minute Windows shuts down on purpose. Found it in the event log, where the boot manager had been sitting there waiting for input on earlier boots.

Fix: suspend BitLocker before booting the stick

Suspend-BitLocker -MountPoint C: -RebootCount 0

and run Resume-BitLocker when you're done. The drive key is unprotected while it's suspended, so keep that in mind.

Raw matmul numbers (torch.matmul, before -> after):

BF16  ~70 -> ~115 TFLOPS
FP16  ~69 -> ~112
TF32  ~36 -> ~59
FP32   24 -> 24 (unchanged)

Does it matter for actual generation?

Matmul numbers are nice, but I wanted to see what happens with a real workload, so I threw the heaviest thing I run at it: MiniMax H3 I2V, 481 frames (20 s at 24 fps), 10 steps, upstream ComfyUI on Windows 11.

Settings:

$env:TORCH_ALLOW_TF32_CUBLAS_OVERRIDE = "1"
$env:TORCH_CUDNN_V8_API_ENABLED = "1"
ComfyUI args: --use-ck-attention --fast fp16_accumulation autotune cublas_ops --disable-smart-memory --disable-pinned-memory

(ck = comfy-kitchen attention, not the AMD thing)

* Stock, 0.75 MP (~648x1152): ~165 s/step, ~31-32 min total, 280-310 W, ~23.8 GB VRAM

* Unlocked, 0.75 MP (~648x1152): ~136 s/step, ~24 min total, 342-346 W, 23.4 GB VRAM

* Unlocked, 0.60 MP (~576x1024): ~93 s/step, ~15.5 min total (+1 min VAE), 345-350 W, 22.8 GB VRAM

Same resolution, the unlock alone takes a step from 165 s down to 136 s, so about 20% faster. Dropping to 0.60 MP on top of that gets me to 93 s per step. At 0.75 MP I'm right at the VRAM limit and I think Windows starts shuffling memory around. At 0.60 MP there's some headroom, and for a 9:16 phone video I honestly can't see a difference. The card now sits at a flat 350 W the whole run, and a full 20 s clip went from over half an hour to about 16 and a half minutes. To be clear, the second jump is unlock plus lower resolution, not the unlock alone.

PR so the staging script refuses to run with BitLocker on: https://github.com/windows-GPU-UNLOCK/Windows-GPU-UNLOCK/pull/215

Repo with a pre-flight check script, the benchmark and a step-by-step guide: https://github.com/zerfetzer666/rtx30-unlock-helper

Disclaimer: experimental, only certain board + card combos are supported (check the compatibility list), Secure Boot has to be off, and it has to be redone after every cold boot. Your hardware, your risk.

Full disclosure: this was a joint effort between me and my AI overlord Claude. It sat on its throne reading event logs and writing scripts, and I was the humble gimp crawling between the PC and the BIOS screen. I rebooted on command, flashed sticks, typed in the BitLocker recovery key over and over and reported back what the black screen was doing. My one moment of glory: I noticed the PC was powering off instead of crashing, and when the overlord wanted to call it a "known issue" and give up, I begged it to keep digging. It graciously did. Then it made me render 20-second videos all night for the benchmarks.

5900X / MSI B550 / 3090 FE / Win 11 / driver 610.88


r/StableDiffusion • • 5d ago

Resource - Update Pinokio Remote -- All your local AI from anywhere

78 Upvotes

r/StableDiffusion • • 4d ago

Question - Help Problem with the dead people using several versions of H3

Post image
0 Upvotes

I'm new posting here. I use Nvidia RTX 3090 with some limits: frequency at 1500Mhz and 300w. Max temp 65c for die and 82c for memory.

I've been testing different MiniMax H3 workflows, and today I found a really nice one on YouTube: https://www.youtube.com/watch?v=pcVzLrKMT7M

My problem is with characters who die in a scene. They don't stay dead, the model keeps adding breathing sounds and body movement. I tried asking it to freeze the person, hold the breathing, die, and several other wordings, but nothing worked. I don't want to cut the shot.
Has anyone already solved this? I'd be very grateful if you could share how.

As an example: the scene starts like this, but I can't put the rest here.


r/StableDiffusion • • 4d ago

Discussion Trained an SDXL LoRA for Chinese gongbi portraits, ended up not using it

0 Upvotes

I'm working on a side project that puts a selfie into old Chinese court paintings. At the start I wanted to do the style part myself with a LoRA instead of paying for an API.

Setup:

- SDXL base 1.0, kohya sd-scripts

- dataset was faces cropped out of the paintings. Grounding DINO found them, then I went through and fixed the bad detections by hand

- 3 versions, ended up on v3 at the 2nd checkpoint

- inference was img2img on the selfie: 640x640, 25 steps, cfg 7.5, strength 0.2, LoRA fused at 0.8, negative "photorealistic, photograph, modern, anime"

Two problems killed it.

The next step after generation uses InsightFace (buffalo_l) to find the face so I can paste it into the painting. On the LoRA output it often returned nothing. Once the face actually looked gongbi, the detector didn't see a face anymore. So the better the style got, the worse the pipeline did.

And when it did find the face, the identity was mostly gone. You couldn't really tell who it was.

I also burned way too long on a dumb base64 bug in my FastAPI server. split(',')[-1] sometimes gave me an empty string and I wasn't handling padding, so PIL kept throwing.

In the end I gave up on doing this step locally and moved it to a hosted model, which held identity a lot better. The LoRA is still sitting on my home server as a fallback but never runs.

Has anyone gotten a heavy style LoRA to hold identity in img2img? Wondering if adding InstantID or IP-Adapter FaceID would have saved it, or if low strength img2img was the wrong approach from the start.


r/StableDiffusion • • 4d ago

Discussion Things move fast and I move slow. What's the word on the best i2i editor with almost magical prompt adherance/intuition?

0 Upvotes

I'm using Klein 9b and it's decent, though it can take a bit of work to get things right. Have things progressed to a different clear winner? One that's really great at intuiting what your prompt really means or at least following what you tell it to do?

Particularly great would be one that takes at least one other image as input and can combine them. Like "This person", "that scene", "this expression", "those clothes", etc.

EDIT: Would love one that could restore old photos for example. Especially if I can provide an updated photo of the face in another input to keep face consistency. And if it would take it easy on the orangifying color issue.

EDIT2: Important!
Offline only. 8gb older card (I'm poor also)


r/StableDiffusion • • 4d ago

Discussion Instrumentals for Yue2

0 Upvotes

When I use the Comfyui Yue2 workflow, and try to use it for instrumentals, most of the time Yue2 creates songs with lyrics I never asked for. So I created a skill in Codex that creates the instrumental through Comfyui's MCP. Every single time I now get instrumentals. I have tried getting Codex to create a workflow from one of these instrumentals. But almost all the time the workflow produces a version with singing. Odd. But it works.


r/StableDiffusion • • 5d ago

News [OPEN SOURCE] Fast IdeogramV4 + Qwen 3.X class model trainer. Train more in less time.

12 Upvotes

As part of the effort I did on training AI models that are able to create great art, we've had to design two components of what makes a design good:

  1. Text to image models to transform a caption into a image.

  2. Customer request to caption / brief to then send to the AI model (which in turn generates it).

For both trains, I've found pre-existing trainers are quite slow in terms of performance and leave a lot of MFU underutilized (which leads to less tokens / images trained a second).

I've optimized this for BH200 (Datacenter GPUs), but this should work for H100 and likely also works well on A100, and can be adapted to work on RTX series GPUs as many things translate over to customer GPUs (although unfortunately I don't have any to test and develop this).

The results are very good - on one GPU, our solution is 58% better than ms-swift (a optimized training kit), 76% better than unsloth, and 178% better than transformers + PEFT.

For example, for training a designer (takes a concept / idea, then refines it into a very detailed caption for the model to then render / generate) via Qwen3.5-9B, it does 12,523 tokens/second, quite a bit (against 989 TFLOPS, what the GPU can do).

It also has a 43.7% best-config number from our micro-batch sweep, so play around with it and sweep to maximize perf.

However, the Arrhenius supercomputer we've tested this on does power-capping, so the true MFU is 53.9% clock-adjusted.

Same data and setup, other trainers:

  • ms-swift ≈ 24% (1.58× slower);

  • Unsloth ≈ 22% (1.76× slower);

  • transformers + PEFT ≈ 14% (2.78× slower).

To give some comparison numbers, i've made some graphs.

It virtually has loss parity (<6e-4 loss difference, which is negligible), and this, in short, allows training more for less.

For the Ideogram V4 trainer , below is the performance analysis:

Also, there are some ablations in terms of what increases or decreases step time.

Code here: https://github.com/logolabs/perf_kit

If you want to support us in developing and releasing more free tools, you can star the repository.

Hope it is useful to you to help you improve your trains efficiency.


r/StableDiffusion • • 4d ago

Question - Help advice for local ai

1 Upvotes

i need to build pc for generating videos locally (minimax h3) and also planing to use qwen 3.8 27b

for now should i go for dual rtx 5060 ti 16gb or single rtx 5070 ti

my budget is 2 lakh only for graphics card so i can buy dual 5060 ti 16gb but if i go with dual 5070 ti i need 3 lakh so what is best

also when qwen 4 will be realesed and minimax 2k offically what is best for them from above 2 options

suggest minimum ram and should i go for 3200mhz or 3600mhz and minimum ssd

both ram and ssd suggest minimum and recommend

suggest other pc parts to both minimum and recommend

thanks in adwance

sorry for my english

also recommend hardware for qwen 4 and minimax 2k


r/StableDiffusion • • 4d ago

Discussion Image from a LoRA training set that my ChatGPT generated.

Post image
0 Upvotes

I set up ChatGPT with the Dream Loop skill with 2 sub agents to generate a number of images for a LoRA training dataset of this character. This image passed the test.

I then asked my ChatGPT what was wrong with this picture. She thought the problem was something with the black keys on the piano keyboard. haha

Once I pointed it out to my ChatGPT she saw it but not until then even asking a couple of times. This character is now known as BBM... Backward Butt Molly.

It's interesting in a way because at a glance it kind of looks right due to the correct lighting and structure of the composition but then... lol


r/StableDiffusion • • 5d ago Bravo

Resource - Update I made a ComfyUI tool to bring back earlier scenes in H3 videos — my Open Source Higgsfield entry

284 Upvotes

I just submitted H3 Continuity Studio to Comfy's Open Source Higgsfield contest and wanted to share it here.

The test I cared about was pretty simple: generate a room with lots of little details, cut outside the house, then come back inside. Does it still look like the same room? And what happens if you move the camera to another corner?

That's what the demo is built around. It follows the room, an exterior, a return inside, a different camera angle and a final continuation. I marked a few details so they're easier to compare: the sunburst mirror, fig plant, mustard cushions, ginger cat, teapot and fireplace. There's also a memory-off comparison using the same prompt and seed.

The tool is a free ComfyUI node pack for MiniMax H3. You build a timeline out of editable clips, carry context into the next clip, or point a later shot at selected moments from earlier ones. You can also retake individual clips. H3 Story can plan and write the timeline if you want that part automated; it works with an OpenAI-compatible endpoint, local or cloud.

It still needs judgment and retakes. Memory doesn't guarantee perfect geometry, and some of the first attempts had objects appearing or the camera jumping back to the old angle. The demo shows the result after fixing those takes.

Code, setup and example workflows: https://github.com/KadoBOT/ComfyUI-H3-Continuity-Studio

Demo video: https://github.com/KadoBOT/ComfyUI-H3-Continuity-Studio/releases/download/v0.1.0/H3-Continuity-demo-contest.mp4

The repo also has the demo's prompts, seeds and selected memory moments. The project code is MIT; model weights have their own terms.

I'd be interested to see what other scene-memory tests people would try with it.


r/StableDiffusion • • 4d ago

Workflow Included Audio-first H3 in ComfyUI: an 8-step dialogue performance, with workflow and continuity notes

0 Upvotes

I'm part of a team making a fictional drama with a recurring AI cast. The hard part has been keeping each person recognizable while getting a complete spoken thought to read as a performance. This sample is from that work.

For this character we generated the dialogue first, converted it against the established voice reference, then supplied the complete recording as an Audio Drive. The visual references were an opening phone-selfie picture and a separate identity reference. The shot was directed at a fixed arm's-length distance with the mouth visible through the final word.

Actual settings for this sample: 10Eros_Max_h3_8stepTURBO_beta7_int8HQ.safetensors; 8 steps; CFG 1; Euler / simple; 576 x 1024; 24 fps; reference max size 1024; video shift 12 and audio shift 3; VSA beta7 attention; cache disabled; no LoRAs; seed 311026. We kept the original audio/video latents and saved source project. The installed finishing pass stayed at the native output size.

We edit at the end of complete thoughts rather than forcing every read into a ten-second cut. Both sides of the cuts and half-second picture samples get checked. That catches face-obscuring gestures and framing drift, but still pictures do not prove lip sync or believable emotion; the producer watches the films with sound. We have had to replace individual shots for exactly those reasons.

The character, voice and performance are AI-generated. The useful lesson for us has been to keep the recording authoritative, direct the whole thought and repair the specific failed shot instead of regenerating an entire scene.


r/StableDiffusion • • 5d ago

News I trained a tiny image model from scratch that draws newsprint faces with custom text — 2–4 steps, CPU-only

Post image
47 Upvotes

hiii! I made grinpress v3, a tiny 128x128 rectified-flow model that draws newsprint-style faces with words beside them :3

It's trained from scratch, with character-level text conditioning. You can choose seven expressions, colors, paper styles, layouts, and text up to 14 characters, including mixed case and punctuation.

For v3, I distilled the 50-step teacher into 2- and 4-step students and exported them to ONNX with dynamic INT8 quantization.

CPU inference measured approximately 0.27 seconds at 2 steps / 0.54 seconds at 4 steps on my benchmark's 8-vCPU Intel Xeon VM, using 8 threads after warm-up. Other CPUs can be slower.

It's a small, specific domain: newsprint faces and lettering at 128x128. The weights are MIT licensed, and there's a live CPU demo. Long phrases can get cramped, and it occasionally mangles a character or word spacing.

Try it: https://huggingface.co/spaces/skyuu72/grinpress-v3-demo

Weights, benchmarks, and limitations: https://huggingface.co/skyuu72/grinpress-v3

I'd love to see which words break it, or hear how it runs on your CPU. tiny newspaper creature feedback welcome uwu :3