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v6.12.0

InvokeAI v6.12.0

This is a feature release of InvokeAI which provides support for multiple accounts on the same InvokeAI backend, enhanced support for the Z-Image and FLUX.2 models, multiple user interface enhancements, and new utilities for managing models.

[Jump to Installing and Updating]

Multi-User Mode (Experimental)

Have you ever wished you could share your InvokeAI instance with your friends, family or coworkers, but didn’t want to share your galleries or give everyone the ability to add and delete models? Now you can. InvokeAI 6.12 introduces an experimental multi-user mode that allows you to create separate user accounts with login names and passwords. Each account’s image boards, images, canvas state and UI preferences are separate from the others. Users with administrative privileges are allowed to perform system-wide tasks such as adding and configuring models and managing the session queue, while ordinary users are prevented from making this type of change.

InvokeAI Log-In Screen

See the Multi-User Mode User’s Guide for information on setting up and using this mode.

Multi-User mode was contributed by @lstein .

Enhanced Support for Z-Image and FLUX.2 Models

Z-Image Base — This version of InvokeAI adds support for the Z-Image Base model family. This is an undistilled version of Z-Image suitable for fine-tuning and LoRA training. It also provides a high level of image diversity while preserving excellent image quality.

FLUX.2 LoRAs — InvokeAI now supports a variety of FLUX.2 Klein LoRA formats.

Thanks to @Pfannkuchensack for his work on these enhancements.

Paged Gallery Browsing — Paged gallery browsing is back. Go to image board settings and select “Use Paged Gallery View” to replace infinite gallery scrolling with page-by-page navigation.

image

Arrow Key Navigation — The arrow keys now work correctly when browsing a gallery. When the Viewer is in focus, the right and left arrow keys will navigate through the currently selected gallery. When the gallery thumbnails are in focus, the right/left/up/down arrows navigate among them.

@DustyShoe contributed these enhancements.

New Canvas Features

The Canvas now features several new features added by @DustyShoe

Text Tool — The Canvas now features a Text tool that allows you to insert text in a variety of fonts, sizes and styles, move it around the canvas, and commit it to the raster layer.

Linear and radial gradient tools — These new tools add radial and linear gradients to the Canvas. The gradients use color transparency and the foreground/background colors to draw gradients in the direction of the mouse movement.

image

Invert Button for Regional Guidance Layers — You can now select any Regional Guidance region and select the “invert” button to exchange painted regions with unpainted ones and vice versa. As an added bonus, the invert button also works with Inpaint Masks.

Layer Controls Moved The controls for creating, duplicating and deleting canvas layers have been moved from the top of the layers list to the bottom, which is more consistent with how other graphics packages position their layer controls and, we think, more intuitive. Long-term Canvas users may need to adjust to the new positioning.

A few improvements contributed by @lstein aim to make it easier to maintain the model and image databases.

Remove Orphaned Models — Over time InvokeAI may accumulate unused “orphan” models in its models directory that take up space but have no entries in the models database for one reason or another. This means they take up disk space without being usable. A new “Sync Models” button in the Model Manager detects and offers to delete such orphaned models. Developers and other users who have access to the source code repository will also find a script, located in scripts/remove_orphaned_models.py , that will do the same thing from the command line.

Remove Dangling Models — The converse problem occurs when a model directory, or one of its files, was removed or renamed externally, causing it to be referenced in the models database but not be usable. There is now a “Missing Files” filter option in the Model Manager that will identify models that are damaged or deleted. You can then select the models you wish to delete and remove them from the database. In addition, the model selection menus will no longer display models that are missing or broken.

Gallery Maintenance Script — For users with access to the source code repository, the scripts/gallery_maintenance.py python script will clean up dangling and orphaned gallery images. Dangling images are those that appear in the Invoke gallery database but whose files have been deleted from disk. Orphaned images are those that have files on disk but are missing from the database. A related database maintenance tool with more bells and whistles can also be found in @Pfannkuchensack ‘s GitHub at https://github.com/Pfannkuchensack/sqlite_invokeai_db_tool.

Workflow Iterator Improvements

@JPPhoto fixed the way that workflow collections work. Previously when you created a Collection and passed it to an iterator, the items in the collection would be passed to downstream nodes in an unpredictable order. Now, the order of items in the collection is preserved, making complex workflows more predictable and reproducible.

Remote Controlling Invoke’s Generation Parameters

It is now possible to programmatically set Invoke’s generation parameters using a new REST endpoint. This allows a script or other external program to select the model, image size, seed, steps, LoRAs, reference images, and all the other parameters that go into a generation. For documentation of the feature see:

@lstein added this feature.

Translations

Thanks to @Harvester62 for providing the Italian translations for this release.

Installing and Updating

The Invoke Launcher is the recommended way to install, update and run Invoke. It takes care of a lot of details for you - like installing the right version of python - and runs Invoke as a desktop application.

Note: With recent updates to torch, users on older GPUs (20xx and 10xx series) will likely run into issues with installing/updating. We are still evaluating how we can support older GPUs, but in the meantime users have found success manually downgrading torch. Head over to discord if you need help.

Follow the Quick Start guide to get started with the launcher.

If you don’t want to use the launcher, or need a headless install, you can follow the manual install guide.

Behind-the-Scenes Improvements

This release are contains a number of bug fixes and performance enhancements.

  • Optimize cache locking in Klein text encoder — (@girlyoulookthebest) This addresses a race condition in the Model Cache which prematurely removed the FLUX.2 Klein encoder from memory.
  • Run Text Encoder on CPU — (@lstein) This is an option available in the details panel of the Model Manager that allows you to force large text encoder models to run on CPU rather than GPU. This preserves VRAM for use by the denoiser steps and in some cases improves performance. Thanks to @girlyoulookthebest who found and fixed a bug in this feature.
  • Fix IP Adapters losing their model path — (@Pfannkuchensack) Fixes the Model Manager’s “reidentify” function when run on IP Adapter models.
  • Kill the server with a single ^C — (@lstein) When previous version of Invoke were launched from a command-line terminal, it used to require two key board interrupts (control-C) to completely shut it down. This is now fixed.
  • Persist the selected board and image across browser sessions — (@lstein) The last image board selected is now restored when you edit a browser session and restart it.

Detailed Change Log

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.11.0…v6.12.0

InvokeAI 6.13.0

This release of InvokeAI offers support for a variety of new models, including those that are remotely hosted by external providers such as GPT Image. In addition, it provides a host of new and improved features as well as bug fixes.

Installation

See Installation for installation instructions and troubleshooting.

What’s New

New Locally-Hosted Models

We’ve added support for the popular Qwen Image models, both the txt2img and edit versions, as well as Anima.

Qwen Image 2.5

This is a high quality txt2img model that can be run either on your local hardware are on a remotely hosted service (see Hosted Models. We provide starters for the full model (~40 GB!) as well as multiple smaller quantized models. For best results, we recommend 30-40 steps and a CFG of 3-4. We also provide two “turbo” LoRA models, Qwen Image Lightning (4-steps) and Qwen_Image_Lightning (8-steps). These LoRAs provide fast rendering and high accuracy, but loss of diversity. Use a CFG of 1 and a Shift of 3 when applying either of these LoRAs.

Qwen Image Edit 2.5

This is a version of Qwen Image that is optimized for image editing. Add up to three reference images and tell the model on how to combine and alter them using declarative statements such as “Pose the duck on the table”. We provide the full model as a starter, along with multiple quantized versions and two Qwen Image Edit Lightning LoRAs for turbo mode.

See Qwen-Image-Edit: Image Editing with Higher Quality and Efficiency for tips on using Qwen Image Edit effectively.

Anima Preview 3

Anima is an anime-themed model created by a collaboration between CircleStone Labs and Comfy Org. It is able to produce a wide variety of illustration styles. There is also an Anima Turbo LoRA that can be used to speed up rendering using a CFG of 1 and 8-12 steps.

You’ll find Anima and its support models in the Starter Models tab.

New Externally-Hosted Models

This version of InvokeAI offers the ability to generate using externally-hosted models, such as those provided by OpenAI, Google and cloud-based AI generation hosting services. You “install” these models by providing an API key provided by a service that you subscribe to. Typically image generation services will provide a number of generations for free and then start charging on a pay-as-you-go basis. We support externally-hosted models from OpenAI, Gemini (Google), BytePlus, and Alibaba Cloud.

An externally-hosted model works much like a locally-hosted one but with restrictions. In general, you cannot adust steps, scheduler or CFG, and only a limited number of image dimensions are supported. Both txt2img and img2img modes are supported, and the models can be applied to the Canvas and Workflow editor. However inpainting, outpainting, controlnets, LoRAs, regional guidance, and the ability to apply different levels of denoising to img2img are not available. These are limitations imposed by the hosting service and not by InvokeAI.

To get started with externally-hosted models, go to the Models tab and select External Providers. Select the hosting service you wish to use and enter your API key. Click Save and the models supported by this provider will be added to your collection of models.

Models available from OpenAI

  • GPT Image 1
  • GPT Image 1.5
  • GPT Image 1 Mini
  • DALL-E 3

Models available from Gemini (Google)

  • Gemini 2.5 Flash Image
  • Gemini 3 Pro Image Preview
  • Gemini 3.1 Flash Image Preview

Models available from BytePlus

  • Seedream 3.0 T2I
  • Seedream 4.0
  • Seedream 4.5
  • Seedream 5.0 Lite

Models available from Alibaba Cloud

  • Qwen Image 2.0 Pro
  • Qwen Image 2.0
  • Qwen Image Max
  • Qwen Image Edit Max
  • Wan 2.6 Text-to-Image

Model Manager Improvements

This version improves the Model Manager in several ways. When installing a new model, the installation queue display and progress bars have been completely rewritten to be more functional and attractive. A new bulk reidentify action has been implemented, and it is now possible to sort the model listing in multiple ways.

Image Generation Improvements

Users now have access to LLM-powered prompt expansion and image-to-prompt features. You will find two new buttons in the prompt textfield:

  • Expand Prompt uses a local TextLLM model to expand brief prompts into detailed image generation prompts. This button will replace a simple prompt with a complex one that is well-suited for producing high quality imagery.
  • Image to Prompt Generates descriptive prompts from uploaded images. Use it as a supplement to reference images.

To use these features, you must first install a causal LM model, such as Qwen/Qwen2.5-1.5B-Instruct via the Model Manager (enter this repo name into the HuggingFace tab). The LLaVA vision model needed for image to prompt should already be installed.

In addition, this release corrects many small bugs and performance bottlenecks in image generation.

You can now automatically create “virtual” boards that group images according to their characteristics. The only grouping currently available is by date, but more options are on their way.

Canvas Improvements

There have been several new features added to the Canvas. One frequently-requested feature is the ability to hide and show the preview stage thumbnails that can obscure the bottom of the canvas. Another feature is the addition of a Lasso Tool with freehand and polygon modes for creating inpaint masks and selecting raster image regions.

Also among multiple new features is the ability to apply custom workflows directly to a Canvas image. First create a workflow with an image input field in the Form Builder and a Canvas Output node. Right click on the canvas and select Run Workflow. The workflow will run on the input image and create a new layer containing the output of the Canvas Output node.

Workflow Editor and Nodes

There is now a Custom Node Manager tab in the left-hand panel which allows you to install and manage related groups of nodes organized into node packs. Node packs can be installed from local files or URLs.

When adding a node to a workflow, you will find that the nodes are now organized by function with an easy to navigate node picker. Another convenient new feature is the workflow connector, a new type of edge that can be used to connect two or more input/output fields in a highly flexible fashion. To start using this feature, right click on the canvas and select Add Connector.

Internally the workflow execution engine has been overhauled and optimized to improve performance and stability. In addition, there are a number of new user-visible features. There are new generation nodes for running external models, new denoising nodes for the Qwen Image and Anima local models, and a node for decoding invisible watermarks in images. The Collect node now supports chaining to enable deterministic iteration over the items in a collection. A new If mode allows for conditional branching of workflows.

Multiuser Features

When running in Multiuser Mode each logged-in user can create private (only visible to the owner), shared (writable by the owner, readable by everyone else) and public (read/write for everyone) image boards. Similarly, users can now create private and shared workflows.

Documentation

The Documentation Site has been completely redesigned and overhauled.

What’s Changed in Detail

Below is a log of all changes from the previous version. Many thanks to all the authors who contributed to this release.

Models and Model Manager

Image Generation

Image Gallery & Image Storage

Canvas

Workflow Editor and Nodes

Multiuser

Internationalizaton

Thanks to Dmitry Warkentin, Gohsuke Shimada, and Riccardo Giovanetti (@Harvester62) for contributing Russian, Japanese, and Italian translations, respectively.

Documentation

Miscellaneous

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.8.0…v6.13.0

InvokeAI v6.13.5

This is a maintenance release of InvokeAI focused on bug fixes and stability. Version 6.14.0 will be the next major feature release, featuring video generation, multiple GPU support, the Wan 2.2 image and video models, pressure-sensitive canvas, HiDiffusion integration, workflow to workflow calls, and much more.

Here are the highlights of the current release:

Updated Libraries

  • React version 19 (frontend support) @joshistoast
  • ROCm version 7.1 (AMD GPU support) @lstein @heathen711
  • Transformers version 5.5.4 (AI inference and training support) @kappacommit

Major Bug Fixes

  • Fix the image viewer progress preview behavior when selecting a gallery image during image generation. @JPPhoto
  • Save and restore both positive and negative prompt history for SD images. @DustyShoe
  • Fix crash when a LoRA was applied to a Flux.2 4B/9B Diffusers model loaded with FP8 storage. @Pfannkuchensack
  • Restore the X/Y queue badges when running in multiuser mode. @lstein
  • Prevent main panel from being squeezed out of existence on small screens. @lstein
  • Gallery maintenance script updated to correctly handle nested image subfolders when structured image directory activated. @lstein
  • Fix crash when using a Z-Image model with regional guidance. @Pfannkuchensack
  • Prevent crash when Heun (2d order) sampler applied to a FLUX.2 Klein model with reference images. @Pfannkuchensack
  • Prevent hang when an unknown wildcard was passed to the dynamic prompt processor. @Pfannkuchensack

New Features

  • Support PEFT named-adapter LoRAs. @Pfannkuchensack
  • Add Qwen Image single-file checkpoint loader with fp8 support. @Pfannkuchensack

Documentation

  • Added information on 3d party GPU providers that host InvokeAI. @lstein @michaelmanly
  • Fix uvicorn URL. @fishd72
  • Add graph execution example to API guide. @wunianze666-netizen

Full List of Changes

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.13.0…v6.13.5

InvokeAI v6.13.6

This is a patch release.

It corrects a bug introduced in v6.13.5 that caused Qwen Image and Qwen Image Edit models to crash with a dictionary key error when used with the default single-file Qwen 2.2 VL Encoder.

Please see https://github.com/invoke-ai/InvokeAI/releases/tag/v6.13.5 for information on what’s in this release.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.13.5…v6.13.6

v6.13.7

InvokeAI Version 6.13.7

⚠️ This is a security patch release

All recent versions of InvokeAI through 6.13.6 contain a security hole that potentially allows an attacker to recover the contents of the running instance’s invokeai.yaml and api_keys.yaml files. These files can contain sensitive data including API keys for image generation hosting services and API download tokens for HuggingFace and other model download sites.

Your keys/tokens may have been compromised if:

  1. Your invokeai.yaml file contains download API tokens for any model provider (e.g. Civitai, HuggingFace),
  2. Your api_keys.yaml file contains API keys for one or more remote image generation services (e.g. Alibaba, OpenAI),
  3. At any point, you set the listen host to 0.0.0.0 to enable network access to your InvokeAI machine, and
  4. Either you exposed the InvokeAI machine to the Internet, or you share your LAN with untrusted individuals.

In the event that these apply to you, or just to be safe, please upgrade to version 6.13.7 and rotate your API tokens and keys.

👉 Note: The InvokeAI team discourages opening your InvokeAI host to the internet. If you choose to do so, we recommend that 1) you use the multiuser configuration and pick strong passwords; and 2) that you isolate the InvokeAI instance in a Docker container. 👈

Additional security fixes

This patch also closes a series of related but less critical security issues:

  • Leakage of model paths: An attacker could recursively enumerate the paths of all models and model-like files, in an arbitrary directory on the Invoke server’s filesystem.
  • Testing existence of arbitrary paths: An attacker could also determine whether a certain file is present on the Invoke server’s filesystem, even if it wasn’t a model file.
  • Administrator functions available to regular users: In multiuser mode, several functions intended for the use of Administrator users were available for use by unprivileged users. Not an obvious security hole, but a potential problem.

Many thanks to George Chen (@geo-chen), for reporting the original issue.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.13.6…v6.13.7

v6.13.8

InvokeAI Version 6.13.8

⚠️ This is a security patch release

Recent versions of InvokeAI through 6.13.7 contain two security holes:

  1. An attacker can craft a URL payload that overwrites files in the server’s custom nodes directory, allowing for execution of arbitrary code on the next startup. On Windows systems, the hole could allow an arbitrary file to be placed anywhere on the filesystem that the server has access to.
  2. A second bugs allows the server to be tricked into connecting to arbitrary networks and services on the local LAN or the Internet.

Both scenarios are closed by this release, and InvokeAI users are strongly encouraged to upgrade.

Many thanks to Abhinash Singh and Arpit Jain for independently reporting issue #1.

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.13.7…v6.13.8

InvokeAI 6.14.0

This is a big release that adds many new user visible features including:

  • Video generation support via Wan 2.2.
  • Krea.2-Turbo and Raw model support
  • Flux.2 Dev support
  • Ernie Turbo model support
  • Ideogram 4 support
  • Anima controlnets and inpainting
  • Flux.2 PiD support (super resolution up to 4K)
  • Multi-GPU support
  • Native Intel XPU support
  • FP8 support for Anima, Flux.2 Krea Turbo & Raw, and Z-Image Turbo

Video Generation

You can now generate short videos using the Wan 2.2 video model. We support text-to-video, image-to-video (use a still image to initiate the video), and image-to-image-video (interpolate video between two images). Video generation is available through the workflow editor, and includes a series of template workflows that allow you to generate videos and concatenate them together into longer productions. See Video Generation to get started.

New models

We now provide support for Krea.2-Turbo, Krea.2-Raw, Ernie Image Turbo, and Ideogram 4.

These are pure text-to-image models (no image editing capabilities). and LoRA/ControlNet/IPAdapter support is being rolled out in stages. Not all LoRAs will currently load. Please report those that don’t in Issues.

Current capabilities are:

ModelText-to-ImageImage-to-ImageInpaintingOutpaintingNegative PromptingReference ImagesRegional GuidanceLoRAsControlNets
Krea-2-Turbo✅✅✅✅⚠️ needs CFG > 1 (off-spec for Turbo)❌⚠️ positive only✅❌
Krea-2-Raw✅✅✅✅✅ (CFG > 1)❌⚠️ positive only✅❌
Ernie-Image-Turbo✅❌❌❌✅ (CFG > 1)❌❌❌❌
Ideogram-4✅❌❌❌❌❌⚠️ prompt + bbox only❌❌
Anima✅✅✅✅✅ (CFG > 1)❌✅ pos + neg✅✅
Flux.2 Dev✅✅✅✅✅ (CFG > 1)✅✅ pos + neg✅✅

Notes

  • Krea-2-Turbo vs Krea-2-Raw — identical feature support; they share one graph builder. The difference is sampling: Turbo is the distilled checkpoint (~8 steps, guidance disabled, fixed mu), Raw is undistilled (~28 steps, CFG ~4.5, dynamic mu).
  • Krea-2 negative prompting — honored only when CFG > 1. The variant does not gate CFG, so the negative prompt is live on Turbo too, but Turbo is meant to run with guidance off; raising CFG to reach the negative prompt is off-spec and degrades output.
  • Krea-2 regional guidance — regional positive text only. Regional negative prompts, auto-negative, and regional reference images raise “unsupported” warnings on canvas. The denoise node supports masked negative conditioning in workflows; the canvas graph does not wire it.
  • Ernie-Image-Turbo — text-to-image only. The denoise node has no denoise_mask input, so masked modes are impossible and image-to-image is not offered; any non-txt2img mode is rejected at graph build. Global negative prompt and the built-in prompt enhancer are supported.
  • Ideogram-4 — text-to-image only; raster layers or inpaint masks with content block generation before enqueue. There is no negative prompt at any CFG: the sampler uses asymmetric CFG with a zeroed unconditional branch, so the denoise node has no negative conditioning input. Regional guidance contributes a positive prompt plus a bounding box to the structured JSON caption; regional negatives, auto-negative, and reference images are dropped with warnings.
  • Anima ControlNets — via kohya-ss’s ControlNet-LLLite adapters (8–66 MB), available as one-click starter installs: sketch (mixed scribble/HED/lineart/grayscale), depth, scribble, lineart, and pose. Control layers work the same way as for other model families. Note that the depth/scribble/lineart/pose adapters were trained on the Preview3 build and are weaker on Anima Base 1.0 — the mixed-conditioning sketch adapter is the strongest general-purpose choice. Each LLLite model may be applied only once per generation. A separate LLLite Inpaint Adapter (Advanced settings) conditions the model on surrounding image content during inpainting/outpainting for cleaner seams.
  • Reference images — unsupported across all five. Anima is explicitly rejected in the canvas validators; the other four have no IP-adapter model config for their base and no IP-adapter wiring in their graph builders.

Multi-GPU Support

If you are lucky enough to have two or more GPUs installed in your system, you can configure InvokeAI to parallelize generation across the GPUs. Two or more queued generation jobs will execute simultaneously on the GPUs, and the preview screen will be split into tiles to show you the progress of each rendering job. This also works when multiple users are logged in: the system will split GPU time fairly among users in a round-robin fashion. If only one generation is queued, then its model’s text encoder will be run on one GPU and the denoiser will run on another, thereby preventing the denoiser from evicting the encoder from VRAM and speeding up the rendering of subsequent images (credits to jacid23 for this concept).

FP8 Support for reduced VRAM usage

You can now reduce your VRAM usage by activating FP8 support for selected models. This reduces the size of models in VRAM by about 50% with minimal loss of quality. To activate it, select the model of interest from the Model Manager, activate the FP8 slider, and Save. The next time you run the model you should see a dramatic decrease in RAM consumption. FP8 storage can be applied to full main models, single-file transformers, and controlnets.

Other Features

  • Performance improvements:

    • We have improved the VRAM consumption estimates for multiple models, which should reduce the number of OOMs.
    • VAEs can now be run on the CPU, reducing the amount of VRAM contention, similar to the text encoders. You can set this option by selecting the VAE in the Model Manager.
    • Improved support for LoRA sliders. We now support UNet-only sliders. In addition, you can now edit the sliders’ min, max and default values from within the Model Manager.
    • If you are using the experimental Wan 2.2 video feature, you can reduce the amount of VRAM used during the VAE decode phase ,at the expense of some performance, by activating tiled decoding. To do so, add wan_memory_optimization: true to your invokeai.yaml configuration file.

  • Canvas improvements:

    • Pressure-sensitive brush opacity on tablets and touch screens.
    • Fine-grid hint added to move tool.
    • A new transparency lock for Gradients and Shapes.
    • Clip Strokes have been extended to the Bbox and Rect/Oval shapes.

  • Workflow management:

    • Graph execution has been optimized, speeding up complex workflows.
    • There is now a LoRA collection picker node which allows you to stack multiple LoRAs together without adding additional nodes.
    • You can now call one workflow from another, making it easier to create and maintain complex workflows.

And lots more! See below for a complete list of What’s New in this release.

Installation and Upgrading

See Installation for various ways to install and run InvokeAI.

What’s Changed Since 6.14.0 Release Candidate 2

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.14.0-rc2…v6.14.0

What’s Changed Since 6.14 Release Candidate 1

New Contributors

What’s Changed Since 6.13.7

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.13.7…v6.14.0-rc2

Version 6.14.1 Latest

This release fixes a few bugs in version 6.14 and adds a couple of minor features that didn’t make it into the previous release. For a full rundown of recently-added features please see 6.14.0 Release

New Features in this release

  • Workflows can now be screenshot and saved as PNGs (@JPPhoto)
  • Middle clicks in the gallery will now open the media in a new browser tab. Enable Use Middle Click to Open Images/Videos in New Tab in settings to get this feature. (@DustyShoe )
  • Krea-2 LoRAs built with ai-toolkit’s DoRA magnitudes are now supported (@Pfannkuchensack )

Bug fixes

  • More robust handling of Kohya keys (@Pfannkuchensack )
  • Close a security hole in the handling of AlibabaCloud image downloads (@wunianze666-netizen )
  • Improve VRAM memory reservation for VAEs (@Pfannkuchensack )
  • Improve internal memory management at shutdown time (@lstein )

Full change list with pointers to detailed descriptions:

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v6.14.0…v6.14.1

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