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Grok image edit
Edit a source image with a written instruction using Grok. For a first run, upload one source image, describe the changes you want and the features to retain, and keep the supplied defaults: grok-imagine-image, 1K resolution, one result and request seed -1. The example instruction requests anime styling while retaining identity. The output returns the edited images. Model selects among grok-imagine-image, grok-imagine-image-quality and grok-imagine-image-pro. Resolution selects a 1K or 2K output request. Image count requests 1 to 10 edited results from the same reference and instruction. Request seed controls whether the editing request reruns. Keep -1 for randomization or change a nonnegative seed to trigger another request. Results remain nondeterministic even with a fixed seed. Aspect ratio remains automatic. The source allows manual aspect ratios only with multiple connected reference images, while this tool connects one. Increasing image count changes the number of results, not the number of references. A source image is required; this tool has no text-only mode, mask-based editing input or denoise-strength control. Uploaded alpha transparency is not preserved because only the loader's RGB image output is connected.
Minimax H3 INT8/INT6/INT4 ConvRot
Minimax H3 INT8 / INT6 / INT4 ConvRot
FLUX.2 dev image generation
Generate images from a text prompt using the fixed FLUX.2 dev model, with an optional Turbo LoRA mode. No source image is required, and there is no negative prompt input. For a first run, replace the example positive prompt with your subject, composition, lighting and style. Keep output and scheduler dimensions at 1024 × 1024, image count at 1, guidance at 4, sampler at Euler and Turbo mode disabled. Standard mode uses the separate Standard steps setting, initially 20. Run the Pipe to receive the generated image batch. Width and height set output dimensions in pixels and must be multiples of 16. Whenever you change them, set Scheduler width and Scheduler height to the same values: these independent fields control the noise schedule and are not synchronized automatically. Image count sets batch size; larger batches require more memory. Enable Turbo mode to select the fixed Turbo LoRA and Turbo steps together. Turbo steps defaults to 8. Each mode uses only its own step setting; enter an integer from 1 to 4096. Turbo strength affects only the Turbo model branch. Setting strength to 0 leaves Turbo steps selected; disable Turbo mode to return to Standard mode. Advanced controls include prompt guidance, seed, both step counts, Turbo strength and sampler. Seed -1 chooses fresh random noise each run; use a fixed seed when comparing settings. Sampler selection applies in both modes and can change the result at the same seed and step count. The fixed model stack uses flux2_dev_fp8mixed.safetensors in diffusion_models, mistral_3_small_flux2_bf16.safetensors in text_encoders, full_encoder_small_decoder.safetensors in vae, and Flux_2-Turbo-LoRA_comfyui.safetensors in loras. All four are marked MISSING_MODEL in the supplied dependency evidence; ensure they are available before running. Source-provided downloads are https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/diffusion_models/flux2_dev_fp8mixed.safetensors, https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/text_encoders/mistral_3_small_flux2_bf16.safetensors, https://huggingface.co/black-forest-labs/FLUX.2-small-decoder/resolve/main/full_encoder_small_decoder.safetensors, and https://huggingface.co/ByteZSzn/Flux.2-Turbo-ComfyUI/resolve/main/Flux_2-Turbo-LoRA_comfyui.safetensors. Model files are fixed by this Pipe rather than selectable controls.
Inzaniak's Lazy Textual Inversions
You can now get all my LoRAs in one single package if you subscribe to my Patreon (including those not on CivitAI):
Amazing Embeddings - fcNegative + fcPortrait suite
fcNeg is a Negative Embedding. You just install it in the embedding folder and then type fcNeg in the negative prompt. I don't know why it shows two trigger words. Ignore "fcneg-neg"
FLUX image upscale
Enlarge an uploaded image using the workflow's fixed FLUX/Dev and AnimeSharp upscale preset. For your first run, upload a source image and run the Pipe. The image passes through the Ultimate Upscale stage, and the saved upscaled image is returned as the result. The preset selects the FLUX/Dev fp8 bundle and 4x-AnimeSharp.pth. This interface offers only the source-image upload: there is no editable prompt, seed override, model selector, LoRA selector or optional processing mode. Processing settings remain at their source values. The upscaler's filename does not establish the final enlargement factor, and the supplied evidence does not establish an exact output size. No separate face-detailing stage is exposed. Running requires ComfyUI-UmeAiRT-Toolkit and the preset's model assets. The supplied dependency records leave the toolkit, FLUX/Dev bundle and AnimeSharp asset unresolved; automatic installation is not established.
ACE-Step music generator
Describe genre, instruments, mood, and tempo in the music prompt. Supply lyrics and section markers for vocals, or retain [instrumental] and arrangement cues for instrumental music. Lyrics strength controls lyric conditioning and remains available in either mode. The workflow uses zeroed negative conditioning, so there is no separate negative prompt. The source note advises manually transliterating multilingual lyrics and adding language markers such as [zh], [ja], or [ko].
HappyHorse reference to video
Generate one video from two reference images and a prompt describing the subjects, action and camera movement. Upload both reference images, then replace the supplied car-and-driver prompt with a description matching your uploads. For a first run, use an object or scene as Reference image 1 and a person as Reference image 2, following the example's arrangement. Start with 5 seconds, 720P and 16:9, and describe an action that fits the chosen duration. The images feed reference slots 1 and 2; they are not designated start and end frames. The example prompt uses @image1 and @image2, while the source's prompt guidance recommends identifiers such as character1 and character2 for reference characters. Clearly describe each subject and its role in words when adapting the prompt. Choose a duration from 3–15 seconds, resolution of 720P or 1080P, and aspect ratio of 16:9, 9:16, 1:1, 4:3 or 3:4. Select HappyHorse 1.0 or 1.1; the default is 1.0. Seed -1 randomizes each run, while a fixed seed requests the same generation seed. Enable Watermark to request an AI-generated watermark. Generation sends the references and prompt to the provider API, requires configured provider access and incurs provider charges. The Pipe returns one video for preview with automatic format and codec selection. The example's requests for consistent details and smooth motion are creative instructions, not guarantees.
SwitchX Video Edit
Create one edited video clip using SwitchX, guided by a prompt and optional reference image. For a first run, upload a source video, replace the example prompt with your desired look, and keep auto editing mode and 720p resolution. Start time defaults to 0 seconds and duration to 5 seconds. Shorten the duration if needed to stay within the 240-frame limit at your source video's frame rate. Enter auto to isolate the main subject automatically and edit the surrounding scene while preserving unmasked source pixels. Enter fill to regenerate the whole frame while preserving geometry; the subject's original pixels are not preserved, so this mode can change the subject's look or costume. Select and custom require first-frame keyframe or per-frame matte inputs unavailable in this Pipe; use auto or fill. The reference-image stage is disabled by default. Enable it and upload an image to guide the background, lighting or costume. Disable it for prompt-only editing. Provide a nonempty prompt or an enabled reference image; at least one is required. Prompts are limited to 2,000 characters. Start time and duration are in seconds. Duration 0 selects the remaining video, still subject to SwitchX's limits of 240 frames and approximately 2.77 megapixels per frame. Five seconds may exceed the frame limit for some videos. Enable strict duration to raise an error when the requested duration cannot be extracted; otherwise a shorter available clip is allowed. Enter 720p or 1080p for the maximum output resolution. Seed -1 randomizes on each run. Seed controls provider re-running rather than reproducibility; results remain nondeterministic with a fixed seed. The advanced video-output section provides file type and codec choices; keep both automatic for the first run. This Pipe returns the edited video, not SwitchX's separate alpha video. SwitchX uses an external Beeble provider call with provider billing.
CyberRealistic Negative - SDXL
Join The Tinkerer on Whop. Membership gets you early releases, private tools and a bunch of extra stuff.
ACE Step 1.5 music generator
Generate an MP3 music track from a music description and lyrics using ACE Step 1.5 XL Turbo. Describe the genre, instruments, mood, and vocal style, and supply lyrics with optional section markers. Adjust tempo, time signature, lyrics language, and musical key. Output duration and conditioning duration are independent controls in seconds; set them to match when changing track length. One shared seed controls conditioning and audio sampling; -1 selects randomization. Audio code generation is enabled by default and can be toggled, with separate guidance and sampling controls. Additional controls expose batch size, audio sampling settings, sampling shift, and MP3 encoding quality.
Vidu Q2 two-subject video
Generate one video featuring two reference subjects, with prompt-directed action, camera movement and optional generated audio. Upload one reference image for each subject; both uploads are required. Refer to the first as @subject1 and the second as @subject2 in the prompt. This interface supplies one image per subject. The references guide appearance rather than defining exact start or end frames. For a first run, upload both references, adapt the example prompt to their appearance, and keep the 5-second, 16:9, 720p defaults. Describe the setting, each subject's actions and the camera movement. Keep the requested action appropriate to the selected duration. Duration supports 1–10 seconds. Choose 720p or 1080p resolution and landscape, portrait or square framing through Aspect ratio. Movement selects auto, small, medium or large motion amplitude for objects in the frame; specify camera direction in the prompt. Generate audio is enabled by default. Include speech and sound directions in the prompt to request generated speech and background music, or disable it for video without generated audio. Seed -1 randomizes each run; a specified seed requests a particular generation variation. This tool uses the paid Vidu Q2 partner service and sends reference images and generation instructions to the provider. It returns one video for preview in Sweet Tea.
Qwen Image canvas outpainting
Extend an uploaded image on selected sides with prompted scene continuation using Qwen Image and inpainting ControlNet. The output is a resized, composited image with an automatically created padding mask. For a first run, upload an image and replace the example scene continuation prompt with content that fits its subject, lighting and style. The defaults add 200 pixels on the left, top and bottom and none on the right, before resizing the padded canvas to a longest edge of 1536 pixels. Set at least one extension amount above zero. Keep Lightning enabled at strength 1, with 4 steps, CFG 1, denoise 1, Euler and Simple for the initial run. Seed -1 randomizes each run; use a fixed seed to compare settings. Each extension is measured in original-image pixels before resizing. The padded image and its padding mask share the longest-edge target and resize together, retaining aspect ratio. Use a positive target size. The original image is also resampled, so preservation outside the generated region refers to the resized working image rather than the original file's exact pixels. No separate mask upload is needed. The region is derived from directional padding; uploaded alpha and loader edit masks are unused, and output transparency is not preserved. Boundary feathering acts before resizing. Mask expansion then grows or contracts the region in resized-mask pixels: positive values create overlap into the original image, while negative values contract it. Tapered corners affect nonzero expansion. Blur radius controls the Gaussian neighborhood and sigma independently controls its spread. The processed mask guides ControlNet and the final blend; softened boundaries mix original and generated pixels. The padded canvas is encoded and sampled without a separate latent noise mask. Final compositing determines where the generated result is visible, retaining the resized source outside the processed mask. Denoise controls how much of the encoded padded canvas is changed during sampling; lower values retain more initial structure. Control strength adjusts image-and-mask guidance. Guidance start and end are sampling-progress fractions from 0 to 1; keep start below end. The default interval covers the full sampling process. A negative prompt can discourage unwanted content, but has little or no effect at CFG 1. Sampler, scheduler and model-specific sampling shift are independent controls; retain Euler, Simple and shift 3.1 for the first run. Lightning is an optional adapter and starts enabled. Its toggle does not update steps or CFG. When disabling it, manually use the source baseline of 20 steps and CFG 2.5; when enabling it again at strength 1, return to 4 steps and CFG 1. For replacing a selected region inside an existing canvas using an uploaded edit mask, use the separate masked inpainting tool.
Recraft image generation from style references
Generate one to six images from a text prompt using a Recraft style created from four uploaded reference images. All four references are required and contribute to the shared style; they guide visual treatment rather than providing an image-editing canvas. For a first run, upload four references with a consistent look, replace the example image prompt with your subject and composition, and keep Output size at 1024x1024 pixels and Image count at 1. Choose realistic_image for a photographic base or digital_illustration for an illustrated base. Output size must be a Recraft-supported width-by-height value. Use Negative prompt to describe unwanted elements, or leave it blank. Image count supports 1–6 images with the same prompt and reference style. Leave Seed at -1 for a randomized re-run seed. A fixed seed controls re-run behavior but does not make Recraft results reproducible; generation remains nondeterministic. This tool requires access to the Recraft partner API. Reference images and generation inputs are sent to the service, and style creation and image generation use provider-priced calls. Style creation remains part of the connected generation path. Reusing a manually supplied style ID is not an available mode in this Pipe.
Wan 2.1 video outpainting
Expand a video's borders with prompt-guided content using Wan 2.1 VACE, producing a silent generated video. For a first run, upload a source video and enter a scene prompt describing its content, the surroundings to add and any desired motion. Keep the initial padding and generation settings, then adjust the padding on each edge to suit your composition. Padding is measured in source-frame pixels and creates the control canvas and outpainting mask; output width and height independently set the generated resolution. Choose output dimensions of at least 16 pixels in multiples of 16. Choose a positive frame count of 4n + 1, such as the default 81. These requirements are documented here because the dimension and frame-count fields have broad numeric ranges. Output FPS sets playback speed independently of source FPS. The default 81 frames at 16 FPS lasts about 5.1 seconds. Source audio is not carried into the result. Frame count is selected separately from the uploaded video's length; this tool does not promise to preserve the original duration or reproduce source pixels exactly. Advanced controls include unwanted-content prompting, VACE control strength, mask feathering and sampling settings. Seed -1 selects randomization; use a fixed nonnegative seed to reuse sampling noise with otherwise matching settings. Keep generation batch size at 1 for a single-video first run. The fixed CausVid LoRA is enabled by default, paired with 3 sampling steps and CFG 1. Its model and text encoder strengths are separately adjustable; text encoder strength only has an effect if the LoRA contains applicable weights. To use the supported bypass mode, bypass the CausVid stage and change sampling to the documented 20 steps and CFG 6. Bypassing does not change those sampling settings automatically. Video encoding offers automatic or explicit container and codec selection, plus CRF quality control; -1 retains the transport's default quality. Video creation defaults to 8-bit. The source describes optional 10-bit creation as retaining smoother gradients, with possible player or downstream compatibility limitations.
Flux Kontext multi-reference editing
Create an edited image from a primary image and up to two additional references using Flux.1 Kontext Pro. Each run also returns a preview of the assembled reference image sent to generation. For a first run, upload the required Primary image and replace the example Edit prompt with your desired change. Identify the referenced subjects and state what should remain unchanged. Both additional references are enabled initially: upload an image for each enabled reference, or disable any unused reference. Disable both for single-image editing; either additional reference can also be used independently. Keep the default layout initially. The second reference is placed above the primary image, and the third is placed to the right of that assembly. Advanced layout controls set each reference's position, joining-edge size matching, gap in pixels, and gap color. Third reference placement is relative to the primary image alone when the second reference is disabled. These controls change the assembled input, not the generated image's aspect ratio. Set Aspect ratio to the desired output width-to-height ratio, between 1:4 and 4:1. Generation controls include guidance strength and step count; their source defaults are 3 and 50. Seed -1 randomizes each run; a fixed seed reuses the seed setting. Prompt expansion lets the provider elaborate your instructions, but prevents exact repeatability even with a fixed seed. The reference preview accompanies generation; it is not a separate preview-only mode. This workflow uses a partner API and requires configured access and sufficient credits. Uploaded transparency is not preserved because only the image outputs, not the alpha masks, enter the reference assembly.
