# Change Log for SD.Next ## Update for 2025-10-12 - **Models** - [WAN 2.2 14B VACE](https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B) available for *text-to-image* and *text-to-video* and *image-to-video* workflows - [Qwen Image Edit 2509](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) and [Nunchaku Qwen Image Edit 2509](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image-edit-2509) updated version of Qwen Image Edit with improved image consistency - [Qwen Image Pruning](https://huggingface.co/OPPOer/Qwen-Image-Pruning) and [Qwen Image Edit Pruning](https://huggingface.co/OPPOer/Qwen-Image-Edit-Pruning) pruned versions of Qwen with 13B params instead of 20B, with some quality tradeoff - [Tencent FLUX.1 Dev SRPO](https://huggingface.co/tencent/SRPO) SRPO is trained by Tencent with specific technique: directly aligning the full diffusion trajectory with fine-grained human preference - [Nunchaku SDXL](https://huggingface.co/nunchaku-tech/nunchaku-sdxl) and [Nunchaku SDXL Turbo](https://huggingface.co/nunchaku-tech/nunchaku-sdxl-turbo) impact of nunchaku engine on unet-based model such as sdxl is much less than on a dit-based models, but its still significantly faster than baseline note that nunchaku optimized and prequantized unet is replacement for base unet, so its only applicable to base models, not any of finetunes *how to use*: enable nunchaku in settings -> quantization and then load either sdxl-base or sdxl-base-turbo reference models - [HiDream E1.1](https://huggingface.co/HiDream-ai/HiDream-E1-1) updated version of E1 image editing model - [SeedVR2](https://iceclear.github.io/projects/seedvr/) originally designed for video restoration, seedvr works great for image detailing and upscaling! available in 3B, 7B and 7B-sharp variants use as any other upscaler! note: seedvr is a very large model (6.4GB and 16GB respectively) and not designed for lower-end hardware note: seedvr is highly sensitive to its cfg scale (set in settings -> postprocessing), lower values will result in smoother output while higher values add details - [X-Omni SFT](https://x-omni-team.github.io/) *experimental*: X-omni is a transformer-only discrete autoregressive image generative model trained with reinforcement learning - **Features** - **Model save**: ability to save currently loaded model as a new standalone model why? SD.Next always prefers to start with full model and quantize on-demand during load however, when you find your exact preferred quantization settings that work well for you, saving such model as a new model allows for faster loads and reduced disk space usage so its best of both worlds: you can experiment and test different quantizations and once you find the one that works for you, save it as a new model saved models appear in network tab as normal models and can be loaded as such available in *models* tab - [Qwen Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) multi-image editing requires qwen-image-edit-2509 or its variant as multi-image edits are not available in original qwen-image in ui control tab: inputs -> separate init image add image for *input media* and *control media* can be - [Cache-DiT](https://github.com/vipshop/cache-dit) cache-dit is a unified, flexible and training-free cache acceleration framework compatible with many dit-based models such as FLUX.1, Qwen, HunyuanImage, Wan2.2, Chroma, etc. enable in *settings -> pipeline modifers -> cache-dit* - [Nunchaku Flux.1 PulID](https://nunchaku.tech/docs/nunchaku/python_api/nunchaku.pipeline.pipeline_flux_pulid.html) automatically enabled if loaded model is FLUX.1 with Nunchaku engine enabled and when PulID script is enabled - **Compute** - **ROCm** for Windows support for both official torch preview release of `torch-rocm` for windows and **TheRock** unoffical `torch-rocm` builds for windows note that rocm for windows is still in preview and has limited gpu support, please check rocm docs for details - **DirectML** warn as *end-of-life* `torch-directml` received no updates in over 1 year and its currently superceded by `rocm` or `zluda` - command line params `--use-zluda` and `--use-rocm` will attempt desired operation or fail if not possible previously sdnext was performing a fallback to `torch-cpu` which is not desired - **installer** if `--use-cuda` or `--use-rocm` are specified and `torch-cpu` is installed, installer will attempt to reinstall correct torch package - **installer** warn if *cuda* or *rocm* are available and `torch-cpu` is installed - support for `torch==2.10-nightly` with `cuda==13.0` - **Extensions** - [Agent-Scheduler](https://github.com/SipherAGI/sd-webui-agent-scheduler) was a high-value built-in extension, but it has not been maintained for 1.5 years it also does not work with control and video tabs which are the core of sdnext nowadays so it has been removed from built-in extensions: manual installation is still possible - [DAAM: Diffusion Attentive Attribution Maps](https://github.com/castorini/daam) create heatmap visualizations of which parts of the prompt influenced which parts of the image available in scripts for sdxl text-to-image workflows - **Offloading** - improve offloading for pipelines with multiple stages such as *wan-2.2-14b* - add timers to measure onload/offload times during generate - experimental offloading using `torch.streams` enable in settings -> model offloading - new feature to specify which models types not to offload in *settings -> model offloading -> model types not to offload* - **UI** - **connection monitor** main logo in top-left corner now indicates server connection status and hovering over it shows connection details - separate guidance and detail sections - networks ability to filter lora by base model version - add interrogate button to input images - disable spellchecks on all text inputs - **SDNQ** - add `SVDQuant` quantization method support - make sdnq scales compatible with balanced offload - add int8 matmul support for RDNA2 GPUs via triton - improve int8 mamtul performance on Intel GPUs - **Other** - server will note when restart is recommended due to package updates - **interrrupt** will now show last known preview image *keep incomplete* setting is now *save interrupted* - **logging** enable `debug`, `docs` and `api-docs` by default - **logging** add detailed ram/vram utilization info to log logging frequency can be specified using `--monitor x` command line param, where x is number of seconds - **ipex** simplify internal implementation - refactor to use new libraries - styles and wildcards now use same seed as main generate for reproducible results - **api** new endpoint POST `/sdapi/v1/civitai` to trigger civitai models metadata update accepts optional `page` parameter to search specific networks page - **reference models** additional example images, thanks @liutyi - **reference models** add model size and release date, thanks @alerikaisattera - **video** support for configurable multi-stage models such as WAN-2.2-14B - **video** new LTX model selection - replace `pynvml` with `nvidia-ml-py` for gpu monitoring - update **loopback** script with radon seed option, thanks @rabanti - **vae** slicing enable for lowvram/medvram, tiling for lowvram, both disabled otherwise - **attention** remove split-attention and add explicitly attention slicing enable/disable option enable in *settings -> compute settings* can be combined with sdp, enabling may improve stability when used on iGPU or shared memory systems - **nunchaku** update to `1.0.1` and enhance installer - **xyz-grid** add guidance section - **preview** implement configurable layers for WAN, Qwen, HV - update swagger `/docs` endpoint style - add `[epoch]` to filename template - starting `[seq]` for filename template is now higher of largest previous sequence or number of files in folder - **Video** - use shared **T5** text encoder for video models when possible - use shared **LLama** text encoder for video models when possible - unified video save code across all video models also avoids creation of temporary files for each frame unless user wants to save them - unified prompt enhance code across all video models - add job state tracking for video generation - fix quantization not being applied on load for some models - improve offloading for **ltx** and **wan** - fix model selection in **ltx** tab - **Experimental** - `new` command line flag enables new `pydantic` and `albumentations` packages - **modular pipelines**: enable in *settings -> model options* only compatible with some pipelines, invalidates preview generation - **modular guiders**: automatically used for compatible pipelines when *modular pipelines* is enabled allows for using many different guidance methods: *CFG, CFGZero, PAG, APG, SLG, SEG, TCFG, FDG* - **Wiki** - updates to *AMD-ROCm, ZLUDA, LoRA, DirectML, SDNQ* pages - **Fixes** - **Microsoft Florence 2** both base and large variants *note* this will trigger download of the new variant of the model, feel free to delete older variant in `huggingface` folder - **MiaoshouAI PromptGen** 1.5/2.0 in both base and large variants - ui: fix image metadata display when switching selected image in control tab - framepack: add explicit hf-login before framepack load - framepack: patch solver for unsupported gpus - benchmark: remove forced sampler from system info benchmark - xyz-grid: fix xyz grid with random seeds - reference: fix download for sd15/sdxl reference models - fix checks in init/mask image decode - fix hf token with extra chars - image viewer refocus on gallery after returning from full screen mode - fix attention guidance metadata save/restore ## Update for 2025-09-15 ### Highlights for 2025-09-15 *What's new*? Big one is that we're (*finally*) switching the default UI to **ModernUI**, for both desktop and mobile use! **StandardUI** is still available and can be selected in settings, but ModernUI is now the default for new installs *What's else*? **Chroma** is in its final form, there are several new **Qwen-Image** variants and **Nunchaku** hit version 1.0! Also, there are quite a few offloading improvements and many quality-of-life changes to UI and overal workflows And check out new **history** tab in the right panel, it now shows visualization of entire processing timeline! ![Screenshot](https://github.com/user-attachments/assets/d6119a63-6ee5-4597-95f6-29ed0701d3b5) [ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867) | [Sponsor](https://github.com/sponsors/vladmandic) ### Details for 2025-09-15 - **Models** - **Chroma** final versions: [Chroma1-HD](https://huggingface.co/lodestones/Chroma1-HD), [Chroma1-Base](https://huggingface.co/lodestones/Chroma1-Base) and [Chroma1-Flash](https://huggingface.co/lodestones/Chroma1-Flash) - **Qwen-Image** [InstantX ControlNet Union](https://huggingface.co/InstantX/Qwen-Image-ControlNet-Union) support *note* qwen-image is already a very large model and controlnet adds 3.5GB on top of that so quantization and offloading are highly recommended! - [Qwen-Lightning-Edit](https://huggingface.co/vladmandic/Qwen-Lightning-Edit) and [Qwen-Image-Distill](https://huggingface.co/SahilCarterr/Qwen-Image-Distill-Full) variants - **Nuchaku** variants of [Qwen-Image-Lightning](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image), [Qwen-Image-Edit](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image-edit), [Nunchaku-Qwen-Image-Edit-Lightning](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image-edit) - **Nunchaku** variant of [Flux.1-Krea-Dev](https://huggingface.co/nunchaku-tech/nunchaku-flux.1-krea-dev) if you have a compatible nVidia GPU, Nunchaku is the fastest quantization & inference engine - [HunyuanDiT ControlNet](https://huggingface.co/Tencent-Hunyuan/HYDiT-ControlNet-v1.2) Canny, Depth, Pose - [KBlueLeaf/HDM-xut-340M-anime](https://huggingface.co/KBlueLeaf/HDM-xut-340M-anime) highly experimental: HDM *Home-made-Diffusion-Model* is a project to investigate specialized training recipe/scheme for pretraining T2I model at home based on super-light architecture *requires*: generator=cpu, dtype=float16, offload=none, both positive and negative prompts are required and must be long & detailed - [Apple FastVLM](https://huggingface.co/apple/FastVLM-0.5B) in 0.5B, 1.5B and 7B variants available in captioning tab - updated [SD.Next Model Samples Gallery](https://vladmandic.github.io/sd-samples/compare.html) - **UI** - default to **ModernUI** standard ui is still available via *settings -> user interface -> theme type* - mobile-friendly! - new **History** section in the right panel shows detailed job history plus timeline of the execution - make hints touch-friendly: hold touch to display hint - improved image scaling in img2img and control interfaces - add base model type to networks display, thanks @Artheriax - additional hints to ui, thanks @Artheriax - add video support to gallery, thanks @CalamitousFelicitousness - additional artwork for reference models in networks, thanks @liutyi - improve ui hints display - restyled all toolbuttons to be modernui native - reodered system settings - dynamic direction of dropdowns - improve process tab layout - improve detection of active tab - configurable horizontal vs vertical panel layout in settings -> user interface -> panel min width *example*: if panel width is less than specified value, layout switches to verical - configurable grid images size in *settings -> user interface -> grid image size* - gallery now includes reference model images - reference models now include indicator if they are *ready* or *need download* - **Offloading** - **balanced** - enable offload during pre-forward by default - improve offloading of models with multiple dits - improve offloading of models with impliciy vae processing - improve offloading of models with controlnet - more aggressive offloading of controlnets with lowvram flag - **group** - new offloading method, using *type=leaf* works on a similar level as sequential offloading and can present siginificant savings on low-vram gpus, but comes at the higher performace cost - **Quantization** - option to specify models types not to quantize: *settings -> quantization* allows for having quantization enabled, but skipping specific model types that do not need it *example*: `sd, sdxl` - **sdnq** - add quantized matmul support for all quantization types and group sizes - improve the performance of low bit quants - **nunchaku**: update to `nunchaku==1.0.0` *note*: nunchaku updated the repo which will trigger re-download of nunchaku models when first used nunchaku is currently available for: *Flux.1 Dev/Schnell/Kontext/Krea/Depth/Fill*, *Qwen-Image/Qwen-Lightning*, *SANA-1.6B* - **tensorrt**: new quantization engine from nvidia *experimental*: requires new pydantic package which *may* break other things, to enable start sdnext with `--new` flag *note*: this is model quantization only, no support for tensorRT inference yet - **Other** - **LoRA** allow specifying module to apply lora on *example*: `` would apply lora *only* on unet regardless of lora content this is particularly useful when you have multiple loras and you want to apply them on different parts of the model *example*: `` and `` *note*: `low` is shorthand for `module=transformer_2` and `high` is shortcut for `module=transformer` - **Detailer** allow manually setting processing resolution *note*: this does not impact the actual image resolution, only the resolution at which detailer internally operates - refactor reuse-seed and add functionality to all tabs - refactor modernui js codebase - move zluda flash attenion to *Triton Flash attention* option - remove samplers filtering - allow both flow-matching and discrete samplers for sdxl models - cleanup command line parameters - add `--new` command line flag to enable testing of new packages without breaking existing installs - downgrade rocm to `torch==2.7.1` - set the minimum supported rocm version on linux to `rocm==6.0` - disallow `zluda` and `directml` on non-windows platforms - update openvino to `openvino==2025.3.0` - add deprecation warning for `python==3.9` - allow setting denoise strength to 0 in control/img2img this allows to run workflows which only refine or detail existing image without changing it - **Fixes** - normalize path hanlding when deleting images - unified compile upscalers - fix OpenVINO with ControlNet - fix hidden model tags in networks display - fix networks reference models display on windows - fix handling of pre-quantized `flux` models - fix `wan` use correct pipeline for i2v models - fix `qwen-image` with hires - fix `omnigen-2` failure - fix `auraflow` quantization - fix `kandinsky-3` noise - fix `infiniteyou` pipeline offloading - fix `skyreels-v2` image-to-video - fix `flex2` img2img denoising strength - fix `flex2` contronet vs inpaint image selection, thanks @alerikaisattera - fix some use cases with access via reverse-proxy - fix segfault on startup with `rocm==6.4.3` and `torch==2.8` - fix wildcards folders traversal, thanks @dymil - fix zluda flash attention with enable_gqa - fix `wan a14b` quantization - fix reprocess workflow for control with hires - fix samplers set timesteps vs sigmas - fix `detailer` missing metadata - fix `infiniteyou` lora load with ## Update for 2025-08-20 A quick service release with several important hotfixes, improved localization support and adding new **Qwen** model variants... [ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867) - **Models** - [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit) Image editing using natural language prompting, similar to `Flux.1-Kontext`, but based on larger 20B `Qwen-Image` model - [Nunchaku-Qwen-Image](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image) if you have a compatible nVidia GPU, Nunchaku is the fastest quantization engine, currently available for Flux.1, SANA and Qwen-Image models *note*: release version of `nunchaku==0.3.2` does NOT include support, so you need to build [nunchaku](https://nunchaku.tech/docs/nunchaku/installation/installation.html) from source - [SD.Next Model Samples Gallery](https://vladmandic.github.io/sd-samples/compare.html) - updated with new models - **Features** - new *setting -> huggingface -> download method* default is `rust` as new `xet` is known to cause issues - support for `flux.1-kontext` lora - support for `qwen-image` lora - new *setting -> quantization -> modules dtype dict* used to manually override quant types per module - **UI** - new artwork for reference models in networks thanks @liutyi - updated [localization](https://vladmandic.github.io/sdnext-docs/Locale/) for all 8 languages - localization support for ModernUI - single-click on locale rotates current locale double-click on locale resets locale to `en` - exclude ModernUI from list of extensions ModernUI is enabled in settings, not by manually enabling extension - **Docs** - Models and Video pages updated with links to original model repos, model licenses and original release dates thanks @alerikaisattera - **Fixes** - nunchaku use new download links and default to `0.3.2` nunchaku wheels: - fix OpenVINO with offloading - add explicit offload calls on prompt encode - error reporting on model load failure - fix torch version checks - remove extra cache clear - enable explicit sync calls for `rocm` on windows - note if restart-needed on initial startup import error - bypass diffusers-lora-fuse on quantized models - monkey-patch diffusers to use original weights shape when loading lora - guard against null prompt - install `hf_transfter` and `hf_xet` when needed - fix ui cropped network tags - enum reference models on startup - dont report errors if agent scheduler is disabled ## Update for 2025-08-15 ### Highlights for 2025-08-15 New release two weeks after the last one and its a big one with over 150 commits! - Several new models: [Qwen-Image](https://qwenlm.github.io/blog/qwen-image/) (plus *Lightning* variant) and [FLUX.1-Krea-Dev](https://www.krea.ai/blog/flux-krea-open-source-release) - Several updated models: [Chroma](https://huggingface.co/lodestones/Chroma), [SkyReels-V2](https://huggingface.co/Skywork/SkyReels-V2-DF-14B-720P-Diffusers), [Wan-VACE](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B-diffusers), [HunyuanDiT](https://huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers-Distilled) - Plus continuing with major **UI** work with new embedded **Docs/Wiki** search, redesigned real-time **hints**, **wildcards** UI selector, built-in **GPU monitor**, **CivitAI** integration and more! - On the compute side, new profiles for high-vram GPUs, offloading improvements, parallel-load for large models, support for new `torch` release and improved quality when using low-bit quantization! - [SD.Next Model Samples Gallery](https://vladmandic.github.io/sd-samples/compare.html): pre-generated image gallery with 60 models (45 base and 15 finetunes) and 40 different styles resulting in 2,400 high resolution images! gallery additionally includes model details such as typical load and inference times as well as sizes and types of each model component (*e.g. unet, transformer, text-encoder, vae*) - And (*as always*) many bugfixes and improvements to existing features! ![sd-samples](https://github.com/user-attachments/assets/3efc8603-0766-4e4e-a4cb-d8c9b13d1e1d) [ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867) *Note*: Change-in-behavior - locations of downloaded HuggingFace models and components are changed to allow for de-duplication of common modules and switched from using system default cache folder to `models/huggingface` SD.Next will warn on startup on unused cache entries that can be removed. Also, to take advantage of de-duplication, you'll need to delete models from your `models/Diffusers` folder and let SD.Next re-download them! ### Details for 2025-08-15 - **Models** - [Qwen-Image](https://qwenlm.github.io/blog/qwen-image/) new image foundational model with *20B* params DiT and using *Qwen2.5-VL-7B* as the text-encoder! available via *networks -> models -> reference* *note*: this model is almost 2x the size of Flux, quantization and offloading are highly recommended! *recommended* params: *steps=50, attention-guidance=4* also available is pre-packaged [Qwen-Lightning](https://huggingface.co/vladmandic/Qwen-Lightning) which is an unofficial merge of [Qwen-Image](https://qwenlm.github.io/blog/qwen-image/) with [Qwen-Lightning-LoRA](https://github.com/ModelTC/Qwen-Image-Lightning/) to improve quality and allow for generating in 8-steps! - [FLUX.1-Krea-Dev](https://www.krea.ai/blog/flux-krea-open-source-release) new 12B base model compatible with FLUX.1-Dev from *Black Forest Labs* with opinionated aesthetics and aesthetic preferences in mind available via *networks -> models -> reference* - [Chroma](https://huggingface.co/lodestones/Chroma) great model based on FLUX.1 and then redesigned and retrained by *lodestones* update with latest **HD**, **HD Flash** and **HD Annealed** variants which are based on *v50* release available via *networks -> models -> reference* - [SkyReels-V2](https://huggingface.co/Skywork/SkyReels-V2-DF-14B-720P-Diffusers) SkyReels-V2 is a genarative video model based on Wan-2.1 but with heavily modified execution to allow for infinite-length video generation supported variants are: - diffusion-forcing: *T2I DF 1.3B* for 540p videos, *T2I DF 14B* for 720p videos, *I2I DF 14B* for 720p videos - standard: *T2I 14B* for 720p videos and *I2I 14B* for 720p videos - [Wan-VACE](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B-diffusers) basic support for *Wan 2.1 VACE 1.3B* and *14B* variants optimized support with granular guidance control will follow soon - [HunyuanDiT-Distilled](https://huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers-Distilled) variant of HunyuanDiT with reduced steps and improved performance **Torch** - Set default to `torch==2.8.0` for *CUDA, ROCm and OpenVINO* - Add support for `torch==2.9.0-nightly` - **UI** - new embedded docs/wiki search! **Docs** search: fully-local and works in real-time on all document pages **Wiki** search: uses github api to search online wiki pages - updated real-time hints, thanks @CalamitousFelicitousness - add **Wilcards** UI in networks display - every heading element is collapsible! - quicksettings reset button to restore all quicksettings to default values because things do sometimes get wrong... - configurable image fit in all image views - rewritten **CivitAI downloader** in *models -> civitai* *hint*: you can enter model id in a search bar to pull information on specific model directly *hint*: you can download individual versions or batch-download all-at-once! - redesigned **GPU monitor** - standard-ui: *system -> gpu monitor* - modern-ui: *aside -> console -> gpu monitor* - supported for *nVidia CUDA* and *AMD ROCm* platforms - configurable interval in *settings -> user interface* - updated *models* tab - updated *models -> current* tab - updated *models -> list models* tab - updated *models -> metadata* tab - updated *extensions* tab - redesigned *settings -> user interface* - gallery bypass browser cache for thumbnails - gallery safer delete operation - networks display indicator for currently active items applies to: *styles, loras* - apply privacy blur to hf and civitai tokens - image download will now use actual image filename - increase default and maximum ui request timeout to 2min/5min - *hint*: card layout card layout is used by networks, gallery, civitai search, etc. you can change card size in *settings -> user interface* - **Offloading** - changed **default** values for offloading based on detected gpu memory see [offloading docs](https://vladmandic.github.io/sdnext-docs/Offload/) for details - new feature to specify which modules to offload always or never in *settings -> model offloading -> offload always/never* - new `highvram` profile provides significant performance boost on gpus with more than 24gb - new `offload during pre-forward` option in *settings -> model offloading* switches from explicit offloading to implicit offloading on module execution change - new `diffusers_offload_nonblocking` exerimental setting instructs torch to use non-blocking move operations when possible - **Features** - new `T5: Use shared instance of text encoder` option in *settings -> text encoder* since a lot of new models use T5 text encoder, this option allows to share the same instance across all models without duplicate downloads *note* this will not reduce size of your already downloaded models, but will reduce size of future downloads - **Wan** select which stage to run: *first/second/both* with configurable *boundary ration* when running both stages in settings -> model options - prompt parser allow explict `BOS` and `EOS` tokens in prompt - **Nunchaku** support for *FLUX.1-Fill* and *FLUX.1-Depth* models - update requirements/packages - use model vae scale-factor for image width/heigt calculations - **SDNQ** add `modules_dtype_dict` to quantize *Qwen Image* with mixed dtype - **prompt enhance** add `allura-org/Gemma-3-Glitter-4B`, `Qwen/Qwen3-4B-Instruct-2507`, `Qwen/Qwen2.5-VL-3B-Instruct` model support improve system prompt - **schedulers** add **Flash FlowMatch** - **model loader** add parallel loader option enabled by default, selectable in *settings -> model loading* - **filename namegen** use exact sequence number instead of next available this allows for more predictable and consistent filename generation - **network delete** new feature that allows to delete network from disk in *networks -> show details -> delete* this will also delete description, metadata and previews associated with the network only applicable to safetensors networks, not downloaded diffuser models - **Wiki** - Models page updated with links to original model repos and model licenses, thanks @alerikaisattera - Updated Model-Support with newly supported models - Updated Offload, Prompting, API pages - **API** - add `/sdapi/v1/checkpoint` POST endpoint to simply load a model - add `/sdapi/v1/modules` GET endpoint to get info on model components/modules - all generate endpoints now support `sd_model_checkpoint` parameter this allows to specify which model to use for generation without needing to use additional endpoints - **Refactor** - change default huggingface cache folder from system default to `models/huggingface` sd.next will warn on startup on unused cache entries - new unified pipeline component loader in `pipelines/generic` - remove **LDSR** - remove `api-only` cli option - **Docker** - update cuda base image: `pytorch/pytorch:2.8.0-cuda12.8-cudnn9-runtime` - update official builds: - **Fixes** - refactor legacy processing loop - fix settings components mismatch - fix *Wan 2.2-5B I2V* workflow - fix *Wan* T2I workflow - fix OpenVINO - fix video model vs pipeline mismatch - fix video generic save frames - fix inpaint image metadata - fix processing image save loop - fix progress bar with refine/detailer - fix api progress reporting endpoint - fix `openvino` backend failing to compile - fix `zluda` with hip-sdk==6.4 - fix `nunchaku` fallback on unsupported model - fix `nunchaku` windows download links - fix *Flux.1-Kontext-Dev* with variable resolution - use `utf_16_be` as primary metadata decoding - fix `sd35` width/height alignment - fix `nudenet` api - fix global state tracking - fix ui tab detection for networks - fix ui checkbox/radio styling for non-default themes - fix loading custom transformers and t5 safetensors tunes - add mtime to reference models - patch torch version so 3rd party libraries can use expected format - unified stat size/mtime calls - reapply offloading on ipadapter load - api set default script-name - avoid forced gc and rely on thresholds - add missing interrogate in output panel ## Update for 2025-07-29 ### Highlights for 2025-07-29 This is a big one: simply looking at number of changes, probably the biggest release since the project started! Feature highlights include: - [ModernUI](https://github.com/user-attachments/assets/6f156154-0b0a-4be2-94f0-979e9f679501) has quite some redesign which should make it more user friendly and easier to navigate plus several new UI themes If you're still using **StandardUI**, give [ModernUI](https://vladmandic.github.io/sdnext-docs/Themes/) a try! - New models such as [WanAI 2.2](https://wan.video/) in 5B and A14B variants for both *text-to-video* and *image-to-video* workflows as well as *text-to-image* workflow! and also [FreePik F-Lite](https://huggingface.co/Freepik/F-Lite), [Bria 3.2](https://huggingface.co/briaai/BRIA-3.2) and [bigASP 2.5](https://civitai.com/models/1789765?modelVersionId=2025412) - Redesigned [Video](https://vladmandic.github.io/sdnext-docs/Video) interface with support for general video models plus optimized [FramePack](https://vladmandic.github.io/sdnext-docs/FramePack) and [LTXVideo](https://vladmandic.github.io/sdnext-docs/LTX) support - Fully integrated nudity detection and optional censorship with [NudeNet](https://vladmandic.github.io/sdnext-docs/NudeNet) - New background replacement and relightning methods using **Latent Bridge Matching** and new **PixelArt** processing filter - Enhanced auto-detection of default sampler types/settings results in avoiding common mistakes - Additional **LLM/VLM** models available for captioning and prompt enhance - Number of workflow and general quality-of-life improvements, especially around **Styles**, **Detailer**, **Preview**, **Batch**, **Control** - Compute improvements - [Wiki](https://github.com/vladmandic/automatic/wiki) & [Docs](https://vladmandic.github.io/sdnext-docs/) updates, especially new end-to-end [Parameters](https://vladmandic.github.io/sdnext-docs/Parameters/) page In this release we finally break with legacy with the removal of the original [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) codebase which has not been maintained for a while now This plus major cleanup of codebase and external dependencies resulted in ~55k LoC (*lines-of-code*) reduction and spread over [~750 files](https://github.com/vladmandic/sdnext/pull/4017) in ~200 commits! We also switched project license to [Apache-2.0](https://github.com/vladmandic/sdnext/blob/dev/LICENSE.txt) which means that SD.Next is now fully compatible with commercial and non-commercial use and redistribution regardless of modifications! And (*as always*) many bugfixes and improvements to existing features! For details, see [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) > [!NOTE] > We recommend clean install for this release due to sheer size of changes > Although upgrades and existing installations are tested and should work fine! ![Screenshot](https://github.com/user-attachments/assets/6f156154-0b0a-4be2-94f0-979e9f679501) [ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867) ### Details for 2025-07-29 - **License** - SD.Next [license](https://github.com/vladmandic/sdnext/blob/dev/LICENSE.txt) switched from **aGPL-v3.0** to **Apache-v2.0** this means that SD.Next is now fully compatible with commercial and non-commercial use and redistribution regardless of modifications! - **Models** - [WanAI Wan 2.2](https://github.com/Wan-Video/Wan2.2) both 5B and A14B variants, for both T2V and I2V support go to: *video -> generic -> wan -> pick variant* optimized support with *VACE*, etc. will follow soon *caution* Wan2.2 on its own is ~68GB, but also includes optional second-stage for later low-noise processing which is absolutely massive at additional ~54GB you can enable second stage processing in *settings -> model options*, its disabled by default *note*: quantization and offloading are highly recommended regardless of first-stage only or both stages! - [WanAI Wan](https://wan.video/) T2V models for T2I workflows Wan is originally designed for *video* workflows, but now also be used for *text-to-image* workflows! supports *Wan-2.1 in 1.3B* and 14B variants and *Wan-2.2 in 5B and A14B* variants supports all standard features such as quantization, offloading, TAESD preview generation, LoRA support etc. can also load unet/transformer fine-tunes in safetensors format using UNET loader simply select in *networks -> models -> reference* *note* 1.3B model is a bit too small for good results and 14B is very large at 78GB even without second-stage so aggressive quantization and offloading are recommended - [FreePik F-Lite](https://huggingface.co/Freepik/F-Lite) in *7B, 10B and Texture* variants F-Lite is a 7B/10B model trained exclusively on copyright-safe and SFW content, trained on internal dataset comprising approximately 80 million copyright-safe images available via *networks -> models -> reference* - [Bria 3.2](https://huggingface.co/briaai/BRIA-3.2) Bria is a smaller 4B parameter model built entirely on licensed data and safe for commercial use *note*: this is a gated model, you need to [accept terms](https://huggingface.co/briaai/BRIA-3.2) and set your [huggingface token](https://vladmandic.github.io/sdnext-docs/Gated/) available via *networks -> models -> reference* - [bigASP 2.5](https://civitai.com/models/1789765) bigASP is an experimental SDXL finetune using Flow matching method load as usual, and leave sampler set to *Default* or you can use following samplers: *UniPC, DPM, DEIS, SA* required sampler settings: *prediction-method=flow-prediction*, *sigma-method=flowmatch* recommended sampler settings: *flow-shift=1.0* - [LBM: Latent Bridge Matching](https://github.com/gojasper/LBM) very fast automatic image background replacement methods with relightning! *simple*: automatic background replacement using [BiRefNet](https://github.com/ZhengPeng7/BiRefNet) *relighting*: automatic background replacement with reglighting so source image fits desired background with optional composite blending available in *img2img or control -> scripts* - add **FLUX.1-Kontext-Dev** inpaint workflow - add **FLUX.1-Kontext-Dev** **Nunchaku** support *note*: FLUX.1 Kontext is about 2-3x faster with Nunchaku vs standard execution! - support **FLUX.1** all-in-one safetensors - support for [Google Gemma 3n](https://huggingface.co/google/gemma-3n-E4B-it) E2B and E4B LLM/VLM models available in **prompt enhance** and process **captioning** - support for [HuggingFace SmolLM3](https://huggingface.co/HuggingFaceTB/SmolLM3-3B) 3B LLM model available in **prompt enhance** - add [fal AuraFlow 0.2](https://huggingface.co/fal/AuraFlow-v0.2) in addition to existing [fal AuraFlow 0.3](https://huggingface.co/fal/AuraFlow-v0.3) due to large differences in model behavior available via *networks -> models -> reference* - add integrated [NudeNet](https://vladmandic.github.io/sdnext-docs/NudeNet) as built-in functionality *note*: used to be available as a separate [extension](https://github.com/vladmandic/sd-extension-nudenet) - **Video** - redesigned **Video** interface - support for **Generic** video models includes support for many video models without specific per-model optimizations included: *Hunyuan, LTX, WAN, Mochi, Latte, Allegro, Cog* supports quantization, offloading, frame interpolation, etc. - support for optimized [FramePack](https://vladmandic.github.io/sdnext-docs/FramePack) with *t2i, i2i, flf2v* workflows LoRA support, prompt enhance, etc. now fully integrated instead of being a separate extension - support for optmized [LTXVideo](https://vladmandic.github.io/sdnext-docs/LTX) with *t2i, i2i, v2v* workflows optional native upsampling and video refine workflows LoRA support with different conditioning types such as Canny/Depth/Pose, etc. - support for post load quantization - **UI** - major update to modernui layout - add new Windows-like *Blocks* UI theme - redesign of the *Flat* UI theme - enhanced look&feel for *Gallery* tab with better search and collapsible sections, thanks to @CalamitousFelicitousness - **WIKI** - new [Parameters](https://vladmandic.github.io/sdnext-docs/Parameters/) page that lists and explains all generation parameters massive thanks to @CalamitousFelicitousness for bringing this to life! - updated *Models, Video, LTX, FramePack, Styles*, etc. - **Compute** - support for [SageAttention2++](https://github.com/thu-ml/SageAttention) provides 10-15% performance improvement over default SDPA for transformer-based models! enable in *settings -> compute settings -> sdp options* *note*: SD.Next will use either SageAttention v1/v2/v2++, depending which one is installed until authors provide pre-build wheels for v2++, you need to install it manually or SD.Next will auto-install v1 - support for `torch.compile` for LLM: captioning/prompt-enhannce - support for `torch.compile` with repeated-blocks reduces time-to-compile 5x without loss of performance! enable in *settings -> model compile -> repeated* *note*: torch.compile is not compatible with balanced offload - **Other** - **Styles** can now include both generation params and server settings see [Styles docs](https://vladmandic.github.io/sdnext-docs/Styles/) for details - **TAESD** is now default preview type since its the only one that supports most new models - support **TAESD** preview and remote VAE for **HunyuanDit** - support **TAESD** preview and remote VAE for **AuraFlow** - support **TAESD** preview for **WanAI** - SD.Next now starts with *locked* state preventing model loading until startup is complete - warn when modifying legacy settings that are no longer supported, but available for compatibilty - warn on incompatible sampler and automatically restore default sampler - **XYZ grid** can now work with control tab: if controlnet or processor are selected in xyz grid, they will overwrite settings from first unit in control tab, when using controlnet/processor selected in xyz grid, behavior is forced as control-only also freely selectable are control strength, start and end values - **Batch** warn on unprocessable images and skip operations on errors so that other images can still be processed - **Metadata** improved parsing and detect foreign metadata detect ComfyUI images detect InvokeAI images - **Detailer** add `expert` mode where list of detailer models can be converted to textbox for manual editing see [docs](https://vladmandic.github.io/sdnext-docs/Detailer/) for more information - **Detailer** add option to merge multiple results from each detailer model for example, hands model can result in two hands each being processed separately or both hands can be merged into one composite job - **Control** auto-update width/height on image upload - **Control** auto-determine image save path depending on operations performed - autodetect **V-prediction** models and override default sampler prediction type as needed - **SDNQ** - use inference context during quantization - use static compile - rename quantization type for text encoders `default` option to `Same as model` - **API** - add `/sdapi/v1/lock-checkpoint` endpoint that can be used to lock/unlock model changes if model is locked, it cannot be changed using normal load or unload methods - **Fixes** - allow theme type `None` to be set in config - installer dont cache installed state - fix Cosmos-Predict2 retrying TAESD download - better handle startup import errors - fix traceback width preventing copy&paste - fix ansi controle output from scripts/extensions - fix diffusers models non-unique hash - fix loading of manually downloaded diffuser models - fix api `/sdapi/v1/embeddings` endpoint - fix incorrect reporting of deleted and modified files - fix SD3.x loader and TAESD preview - fix xyz with control enabled - fix control order of image save operations - fix control batch-input processing - fix modules merge save model - fix torchvision bicubic upsample with ipex - fix instantir pipeline - fix prompt encoding if prompts within batch have different segment counts - fix detailer min/max size - fix loopback script - fix networks tags display - fix yolo refresh models - cleanup control infotext - allow upscaling with models that have implicit VAE processing - framepack improve offloading - improve prompt parser tokenizer loader - improve scripts error handling - improve infotext param parsing - improve extensions ui search - improve model type autodetection - improve model auth check for hf repos - improve Chroma prompt padding as per recommendations - lock directml torch to `torch-directml==0.2.4.dev240913` - lock directml transformers to `transformers==4.52.4` - improve install of `sentencepiece` tokenizer - add int8 matmul fallback for ipex with onednn qlinear - **Refactoring** *note*: none of the removals result in loss-of-functionality since all those features are already re-implemented goal here is to remove legacy code, code duplication and reduce code complexity - obsolete **original backend** - remove majority of legacy **a1111** codebase - remove legacy ldm codebase: `/repositories/ldm` - remove legacy blip codebase: `/repositories/blip` - remove legacy codeformer codebase: `/repositories/codeformer` - remove legacy clip patch model: `/models/karlo` - remove legacy model configs: `/configs/*.yaml` - remove legacy submodule: `/modules/k-diffusion` - remove legacy hypernetworks support: `/modules/hypernetworks` - remove legacy lora support: `/extensions-builtin/Lora` - remove legacy clip/blip interrogate module - remove modern-ui remove `only-original` vs `only-diffusers` code paths - refactor control processing and separate preprocessing and image save ops - refactor modernui layouts to rely on accordions more than individual controls - refactore pipeline apply/unapply optional components & features - split monolithic `shared.py` - cleanup `/modules`: move pipeline loaders to `/pipelines` root - cleanup `/modules`: move code folders used by pipelines to `/pipelines/` folder - cleanup `/modules`: move code folders used by scripts to `/scripts/