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Three new open-source models just landed in ComfyUI natively: → Gemma 4 (Google DeepMind) - multimodal LLM handling text, image, audio, and video input with built-in step-by-step reasoning mode → VOID (Netflix) - video object removal that also erases shadows, reflections, and physical interactions caused by the removed subject... show more

ComfyUI

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218,749 görüntüleme • 3 ay önce •via X (Twitter)

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In May, we integrated 11 new models spanning image, 3D, audio, video, and multimodal. The highlights: → Krea 2 — style-first image generation, live as a Partner Node on day one. Competes on how the frame looks, not just what's in it → VOID (Netflix) — removes objects and everything they caused: shadows, reflections, physical interactions. Apache 2.0, natively supported → Tripo 3.1 + TripoSplat — one image to a full 3D Gaussian asset, end to end Also live in May: Gemma 4, HidDream-O1-Image, Stable Audio 3, BiRefNet, MoGe, Claude, OpenRouter, Luma UNI-1 Learn more with our blog 👇

In May, we integrated 11 new models spanning image, 3D, audio, video, and multimodal. The highlights: → Krea 2 — style-first image generation, live as a Partner Node on day one. Competes on how the frame looks, not just what's in it → VOID (Netflix) — removes objects and everything they caused: shadows, reflections, physical interactions. Apache 2.0, natively supported → Tripo 3.1 + TripoSplat — one image to a full 3D Gaussian asset, end to end Also live in May: Gemma 4, HidDream-O1-Image, Stable Audio 3, BiRefNet, MoGe, Claude, OpenRouter, Luma UNI-1 Learn more with our blog 👇

ComfyUI

20,064 görüntüleme • 2 ay önce

Stable Diffusion Moment of Audio?? Ace-Step Audio Model just dropped and is now natively supported in ComfyUI. ACE-Step is an open-source music generation model jointly developed by ACE Studio and StepFun.

Stable Diffusion Moment of Audio?? Ace-Step Audio Model just dropped and is now natively supported in ComfyUI. ACE-Step is an open-source music generation model jointly developed by ACE Studio and StepFun.

ComfyUI

23,611 görüntüleme • 1 yıl önce

NEW: Google releases Gemma 4, their most capable open models yet! 🤯 Apache-2.0, multimodal (text, image, and audio input), and multilingual (140 languages)! They can even run 100% locally in your browser on WebGPU. Watch it describe the Artemis II launch! 🚀 Try the demo! 👇

NEW: Google releases Gemma 4, their most capable open models yet! 🤯 Apache-2.0, multimodal (text, image, and audio input), and multilingual (140 languages)! They can even run 100% locally in your browser on WebGPU. Watch it describe the Artemis II launch! 🚀 Try the demo! 👇

Xenova

38,427 görüntüleme • 4 ay önce

🎉Generate. Edit. Repeat. All locally. Flux.1 Kontext [dev] is now open source and fully supported in ComfyUI! Everything below is now enabled: 👉Multi-Step Editing with Context 👉Character Consistency 👉Local Editing 👉Style Reference 👉Object / Background Removal 👉Multiple Inputs 👉Text Editing

🎉Generate. Edit. Repeat. All locally. Flux.1 Kontext [dev] is now open source and fully supported in ComfyUI! Everything below is now enabled: 👉Multi-Step Editing with Context 👉Character Consistency 👉Local Editing 👉Style Reference 👉Object / Background Removal 👉Multiple Inputs 👉Text Editing

ComfyUI

124,177 görüntüleme • 1 yıl önce

FLUX 3 Video is live in ComfyUI via Partner Nodes Black Forest Labs FLUX 3 Model highlights: → 20s in a single generation → native audio, not dubbed on after → text-to-video, image-to-video, keyframes, continuation → multi-scene and multi-angle in one prompt → multilingual dialogue with lipsync that holds → typography that sits in the scene → chain clips agentically for longer stories One model across video, audio, image, and action. Click the link below to download the workflows and learn more with blog

FLUX 3 Video is live in ComfyUI via Partner Nodes Black Forest Labs FLUX 3 Model highlights: → 20s in a single generation → native audio, not dubbed on after → text-to-video, image-to-video, keyframes, continuation → multi-scene and multi-angle in one prompt → multilingual dialogue with lipsync that holds → typography that sits in the scene → chain clips agentically for longer stories One model across video, audio, image, and action. Click the link below to download the workflows and learn more with blog

ComfyUI

24,656 görüntüleme • 7 gün önce

MiniMax H3 is native in ComfyUI, day zero with the weights. Model highlights: → Text-to-video, prompt only → Image-to-video → First-and-last-frame - control the opening frame, the closing frame, or both → Reference-to-video - carry a subject, a motion, or a voice through the clip → In-place editing - modify a shot you already have instead of regenerating it The capability MiniMax (official) leads with is multimodal context understanding, and it's what collapses those five tasks into one model. H3 takes images, audio, and video together and resolves them against a prompt that explains how they relate. Download the workflows & learn more in our blog 👇

MiniMax H3 is native in ComfyUI, day zero with the weights. Model highlights: → Text-to-video, prompt only → Image-to-video → First-and-last-frame - control the opening frame, the closing frame, or both → Reference-to-video - carry a subject, a motion, or a voice through the clip → In-place editing - modify a shot you already have instead of regenerating it The capability MiniMax (official) leads with is multimodal context understanding, and it's what collapses those five tasks into one model. H3 takes images, audio, and video together and resolves them against a prompt that explains how they relate. Download the workflows & learn more in our blog 👇

ComfyUI

226,164 görüntüleme • 10 gün önce

Demis Hassabis on the next 12 Months: - Full multimodal convergence: Models like Gemini will seamlessly take in and output text, images, audio, and video, with cross-pollination that boosts reasoning + creativity. - Breakthrough visual intelligence: Image models like Nano Banana Pro will produce highly accurate infographics and show near-human visual understanding. - Language + video fusion: Video models integrated with LLMs unlock richer analysis, storytelling, and step-by-step visual reasoning. - World models go mainstream like Genie 3 - Agents become reliable

Demis Hassabis on the next 12 Months: - Full multimodal convergence: Models like Gemini will seamlessly take in and output text, images, audio, and video, with cross-pollination that boosts reasoning + creativity. - Breakthrough visual intelligence: Image models like Nano Banana Pro will produce highly accurate infographics and show near-human visual understanding. - Language + video fusion: Video models integrated with LLMs unlock richer analysis, storytelling, and step-by-step visual reasoning. - World models go mainstream like Genie 3 - Agents become reliable

Chubby♨️

89,236 görüntüleme • 8 ay önce

Mattes and Utilities Demo: VFX artist Doug Hogan breaks down a ComfyUI workflow that generates production-ready utility passes directly from your footage. No manual rotoscoping. No guesswork. What's inside: → Prompt-based background removal (RMBG) for fast, clean shots → SAM3 text-prompt segmentation for moving subjects → SAM3 point-based editor for precise matte control → Face segmentation for beauty and skin work in comp → Stable depth and normals passes for relighting and CG integration → App Mode - a simplified UI that hides the node graph entirely Everything ties back to your source plate's native resolution and frame rate automatically via get/set nodes. This is the kind of workflow that used to take a team. Now it runs in ComfyUI. Click the link below for the workflow 👇

Mattes and Utilities Demo: VFX artist Doug Hogan breaks down a ComfyUI workflow that generates production-ready utility passes directly from your footage. No manual rotoscoping. No guesswork. What's inside: → Prompt-based background removal (RMBG) for fast, clean shots → SAM3 text-prompt segmentation for moving subjects → SAM3 point-based editor for precise matte control → Face segmentation for beauty and skin work in comp → Stable depth and normals passes for relighting and CG integration → App Mode - a simplified UI that hides the node graph entirely Everything ties back to your source plate's native resolution and frame rate automatically via get/set nodes. This is the kind of workflow that used to take a team. Now it runs in ComfyUI. Click the link below for the workflow 👇

ComfyUI

26,631 görüntüleme • 2 ay önce

FLUX.2 [klein] 4B + 9B are the newest BFL models in the Flux family—combining image generation + image editing in one compact architecture. Built for interactive workflows and quick iteration, with extremely fast inference on distilled variants. Two models. Two modes. ⚡️

FLUX.2 [klein] 4B + 9B are the newest BFL models in the Flux family—combining image generation + image editing in one compact architecture. Built for interactive workflows and quick iteration, with extremely fast inference on distilled variants. Two models. Two modes. ⚡️

ComfyUI

19,899 görüntüleme • 6 ay önce

Wan2.1-VACE 14B & 1.3B are now natively supported in ComfyUI! This model from Wan brings all-in-one editing capability to your video generation: 🔹Text-to-Video & Image-to-Video 🔹 Video-to-video (Pose & depth control) 🔹 Inpainting & Outpainting 🔹 Character + object reference

Wan2.1-VACE 14B & 1.3B are now natively supported in ComfyUI! This model from Wan brings all-in-one editing capability to your video generation: 🔹Text-to-Video & Image-to-Video 🔹 Video-to-video (Pose & depth control) 🔹 Inpainting & Outpainting 🔹 Character + object reference

ComfyUI

21,517 görüntüleme • 1 yıl önce

In Prompt Engineering for Vision Models, taught by Abby Jacques Verre and Caleb Kaiser of Comet , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for vision models could be text, point coordinates, or bounding boxes, depending on the model. You'll also learn to tune hyperparameters to shape the output. Models you'll use include Segment-Anything Model (SAM), OWL-ViT, and Stable Diffusion. You'll also learn to fine-tune Stable Diffusion to generate personalized images (say, an image of a specific person), using a handful of images for training. As an example of a multi-step workflow, you'll use OWL-ViT to detect an object based on a text prompt, then pass the bounding box to SAM to create a segmentation mask, and input that mask into Stable Diffusion to replace the original object with a new one based on a text prompt. Controlling vision models can be tricky; this course will teach prompting and fine-tuning techniques to get precise control over their output. Get started here:

In Prompt Engineering for Vision Models, taught by Abby Jacques Verre and Caleb Kaiser of Comet , you’ll learn how to prompt and fine-tune vision models for personalized image generation, image editing, object detection and segmentation. The prompts you'll use for vision models could be text, point coordinates, or bounding boxes, depending on the model. You'll also learn to tune hyperparameters to shape the output. Models you'll use include Segment-Anything Model (SAM), OWL-ViT, and Stable Diffusion. You'll also learn to fine-tune Stable Diffusion to generate personalized images (say, an image of a specific person), using a handful of images for training. As an example of a multi-step workflow, you'll use OWL-ViT to detect an object based on a text prompt, then pass the bounding box to SAM to create a segmentation mask, and input that mask into Stable Diffusion to replace the original object with a new one based on a text prompt. Controlling vision models can be tricky; this course will teach prompting and fine-tuning techniques to get precise control over their output. Get started here:

Andrew Ng

151,198 görüntüleme • 2 yıl önce

Introducing A Branding New ComfyUI Look and Native API Nodes! Seamlessly integrate 11 amazing online visual AI models into ComfyUI, including BlackForestLabsAI - Unofficial Flux, MiniMax Design (H3), , Kling AI, Luma, PixVerse, Recraft, Stability AI, Google Veo2, Ideogram, OpenAI GPT image-1, and Pika! 🔹One platform, 11 models, 65 nodes, all at once 🔹Chain the APIs with open models and workflows 🔹No hardware limitation!

Introducing A Branding New ComfyUI Look and Native API Nodes! Seamlessly integrate 11 amazing online visual AI models into ComfyUI, including BlackForestLabsAI - Unofficial Flux, MiniMax Design (H3), , Kling AI, Luma, PixVerse, Recraft, Stability AI, Google Veo2, Ideogram, OpenAI GPT image-1, and Pika! 🔹One platform, 11 models, 65 nodes, all at once 🔹Chain the APIs with open models and workflows 🔹No hardware limitation!

ComfyUI

187,550 görüntüleme • 1 yıl önce

TurboEdit Instant text-based image editing discuss: We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input image and the reconstructed image from the previous step, allowing for correction of the next reconstruction towards the input image. We demonstrate that disentangled controls can be easily achieved in the few-step diffusion model by conditioning on an (automatically generated) detailed text prompt. To manipulate the inverted image, we freeze the noise maps and modify one attribute in the text prompt (either manually or via instruction based editing driven by an LLM), resulting in the generation of a new image similar to the input image with only one attribute changed. It can further control the editing strength and accept instructive text prompt. Our approach facilitates realistic text-guided image edits in real-time, requiring only 8 number of functional evaluations (NFEs) in inversion (one-time cost) and 4 NFEs per edit. Our method is not only fast, but also significantly outperforms state-of-the-art multi-step diffusion editing techniques.

TurboEdit Instant text-based image editing discuss: We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input image and the reconstructed image from the previous step, allowing for correction of the next reconstruction towards the input image. We demonstrate that disentangled controls can be easily achieved in the few-step diffusion model by conditioning on an (automatically generated) detailed text prompt. To manipulate the inverted image, we freeze the noise maps and modify one attribute in the text prompt (either manually or via instruction based editing driven by an LLM), resulting in the generation of a new image similar to the input image with only one attribute changed. It can further control the editing strength and accept instructive text prompt. Our approach facilitates realistic text-guided image edits in real-time, requiring only 8 number of functional evaluations (NFEs) in inversion (one-time cost) and 4 NFEs per edit. Our method is not only fast, but also significantly outperforms state-of-the-art multi-step diffusion editing techniques.

AK

16,062 görüntüleme • 2 yıl önce

LTX-2 is natively supported in ComfyUI on Day 0 🎬🔊 The next chapter in controllability for open-source video generation. - Open-source audio-video foundation model - Generates motion, dialogue, SFX, and music together - Canny, Depth & Pose video-to-video control - Keyframe-driven generation - Native upscaling and prompt enhancement Everything in a single pass.

LTX-2 is natively supported in ComfyUI on Day 0 🎬🔊 The next chapter in controllability for open-source video generation. - Open-source audio-video foundation model - Generates motion, dialogue, SFX, and music together - Canny, Depth & Pose video-to-video control - Keyframe-driven generation - Native upscaling and prompt enhancement Everything in a single pass.

ComfyUI

108,333 görüntüleme • 7 ay önce

The first AI design agent with Nano Banana has dropped. It combines major models for image, video, and 3D asset generation all in one place. You can also edit the images, generate music, and even voiceovers! Step-by-step tutorial 👇

The first AI design agent with Nano Banana has dropped. It combines major models for image, video, and 3D asset generation all in one place. You can also edit the images, generate music, and even voiceovers! Step-by-step tutorial 👇

Alvaro Cintas

158,854 görüntüleme • 11 ay önce

ComfyUI MCP server - A project from Pixelle AI Shoutout to Pixelle-MCP - an amazing open-source project that bridges ComfyUI with LLMs through the MCP protocol. Zero-code, talk to your LLM to iterate ComfyUI workflow! Highlights: - Full TISV (Text, Image, Sound/Speech, Video) support - Flexible deployment options - Easy setup with Docker or one-click scripts - Custom workflow tools in just a few steps 🧵👇

ComfyUI MCP server - A project from Pixelle AI Shoutout to Pixelle-MCP - an amazing open-source project that bridges ComfyUI with LLMs through the MCP protocol. Zero-code, talk to your LLM to iterate ComfyUI workflow! Highlights: - Full TISV (Text, Image, Sound/Speech, Video) support - Flexible deployment options - Easy setup with Docker or one-click scripts - Custom workflow tools in just a few steps 🧵👇

ComfyUI

27,949 görüntüleme • 1 yıl önce

Tracking Anything with Decoupled Video Segmentation paper page: Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary settings. To 'track anything' without training on video data for every individual task, we develop a decoupled video segmentation approach (DEVA), composed of task-specific image-level segmentation and class/task-agnostic bi-directional temporal propagation. Due to this design, we only need an image-level model for the target task (which is cheaper to train) and a universal temporal propagation model which is trained once and generalizes across tasks. To effectively combine these two modules, we use bi-directional propagation for (semi-)online fusion of segmentation hypotheses from different frames to generate a coherent segmentation. We show that this decoupled formulation compares favorably to end-to-end approaches in several data-scarce tasks including large-vocabulary video panoptic segmentation, open-world video segmentation, referring video segmentation, and unsupervised video object segmentation.

Tracking Anything with Decoupled Video Segmentation paper page: Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary settings. To 'track anything' without training on video data for every individual task, we develop a decoupled video segmentation approach (DEVA), composed of task-specific image-level segmentation and class/task-agnostic bi-directional temporal propagation. Due to this design, we only need an image-level model for the target task (which is cheaper to train) and a universal temporal propagation model which is trained once and generalizes across tasks. To effectively combine these two modules, we use bi-directional propagation for (semi-)online fusion of segmentation hypotheses from different frames to generate a coherent segmentation. We show that this decoupled formulation compares favorably to end-to-end approaches in several data-scarce tasks including large-vocabulary video panoptic segmentation, open-world video segmentation, referring video segmentation, and unsupervised video object segmentation.

AK

305,683 görüntüleme • 2 yıl önce

Tutorial: ComfyUI Mattes & Utility Nodes Tutorial for VFX In this video, VFX artist Doug Hogan walks through a ComfyUI workflow for generating production-ready utility passes directly from your footage. No manual rotoscoping required. What's covered: → Prompt-based background removal (RMBG) for fast, simple shots → SAM3 text-prompt segmentation for moving subjects and medium-complexity scenes → SAM3 point-based editor for precise matte control (think: crypto mattes for live action) → Face segmentation for beauty and skin work in comp → Stable depth and normals passes for relighting and CG integration → App Mode — a simplified UI for running all options without touching the node graph All outputs are tied to your source plate's native resolution and frame rate via get/set nodes, so the workflow adapts automatically.

Tutorial: ComfyUI Mattes & Utility Nodes Tutorial for VFX In this video, VFX artist Doug Hogan walks through a ComfyUI workflow for generating production-ready utility passes directly from your footage. No manual rotoscoping required. What's covered: → Prompt-based background removal (RMBG) for fast, simple shots → SAM3 text-prompt segmentation for moving subjects and medium-complexity scenes → SAM3 point-based editor for precise matte control (think: crypto mattes for live action) → Face segmentation for beauty and skin work in comp → Stable depth and normals passes for relighting and CG integration → App Mode — a simplified UI for running all options without touching the node graph All outputs are tied to your source plate's native resolution and frame rate via get/set nodes, so the workflow adapts automatically.

ComfyUI

95,385 görüntüleme • 16 gün önce

ComfyUI API Nodes Wave 2 is LIVE! LLM & 3D API nodes fully unlocked, with more video nodes! Six brand-new APIs just joined ComfyUI: OpenAI GPT-4.1 / 4o / o1 / o3 / o4 Google Gemini 2.5 Pro & Flash Runway Gen-4 Image, Gen-4 and Gen-3 Video Deemos Hyper3D AI - Rodin Tripo Tripo3D V1.4 / 2.0 / 2.5 Vidu AI Vidu (coming soon) Dive in and power up your workflows today!

ComfyUI

22,181 görüntüleme • 1 yıl önce

New short course: Open Source Models with Hugging Face 🤗, taught by Maria Khalusova, Marc Sun, and Younes Belkada! Hugging Face has been a game changer by letting you quickly grab any of hundreds of thousands of already-trained open source models to assemble into new applications. This course teaches you best practices for building this way, including how to search and choose among models. You’ll learn to use the Transformers library and walk through multiple models for text, audio, and image processing, including zero-shot image segmentation, zero-shot audio classification, and speech recognition. You'll also learn to use multimodal models for visual question answering, image search, and image captioning. Finally, you’ll learn how to demo what you build locally, on the cloud, or via an API using Gradio and Hugging Face Spaces. You can sign up here:

New short course: Open Source Models with Hugging Face 🤗, taught by Maria Khalusova, Marc Sun, and Younes Belkada! Hugging Face has been a game changer by letting you quickly grab any of hundreds of thousands of already-trained open source models to assemble into new applications. This course teaches you best practices for building this way, including how to search and choose among models. You’ll learn to use the Transformers library and walk through multiple models for text, audio, and image processing, including zero-shot image segmentation, zero-shot audio classification, and speech recognition. You'll also learn to use multimodal models for visual question answering, image search, and image captioning. Finally, you’ll learn how to demo what you build locally, on the cloud, or via an API using Gradio and Hugging Face Spaces. You can sign up here:

Andrew Ng

224,538 görüntüleme • 2 yıl önce