Image and video generation tools

A set of pipelines that turn an AI coding assistant into a video production line: you describe the video you want in plain language and the agent researches the topic, writes a script, gathers or generates footage, cuts a timeline and renders the result.

Build image, video, audio and 3D generation workflows by connecting blocks on a graph; for creators who want control, on Windows, Linux or macOS.

Install ready-made skills so Claude Code, Cursor or Codex can make short videos, web pages and articles.

OpenCreator (formerly KrillinAI) is a desktop app that bundles AI creator tools into one workspace: write articles or short-video scripts, generate images and video from a prompt (through models like Seedance, Kling, or GPT Image), add AI voiceovers and dubbing, translate and re-subtitle existing videos, and turn a script into a narrated stick-figure animation.

Ask your coding agent to make a promo video for your product and get back a finished MP4 you can keep editing.

Create or edit pictures from written requests with this open weights image model, for developers building image tools.

Create images from text or edit pictures using reference images inside ComfyUI, for people who make images and run ComfyUI themselves.

This repository repackages Alibaba's Qwen-Image-2.1 image generation and editing model as single-file weights formatted specifically for ComfyUI, a popular node-based visual tool for building AI image and video pipelines by connecting boxes on a canvas rather than writing code.

LTX-2.5 is a 22-billion-parameter open-weights model from Lightricks that generates video and sound together: describe a scene in words, or hand it a photo, and it produces a clip with a soundtrack in one pass, so picture and audio stay in sync.

Generate 4–15 second videos with built-in stereo sound from text, images, video or audio, through an online API, web app or desktop app.

Generate images with planned text and object placement using this model for image makers, from written prompts or structured layouts.

Turn a written prompt or a JSON layout into an image, with control over where text and objects go.

Turn short text requests into 8-megapixel images and edit pictures on your own graphics card.

Qwen-Image-2.1 is a 7-billion-parameter image model from Alibaba's Qwen team that both generates pictures from a text description and edits existing ones in the same model, using up to 10 reference images and letting you mark local edits with circles, painted annotations or masks while preserving the identity of people and products shown.

An accelerated 7-billion-parameter image model for making pictures from text and editing an existing image.

Unsloth’s release repackages Qwen-Image-2.1 — the open image-generation model — into GGUF files, the compact format that runs on ordinary computers through tools like llama.cpp and Stable Diffusion.cpp instead of demanding a datacenter GPU.

Viggle’s turbo build is a distilled, faster version of Qwen-Image-2.1, the open image model: where the original takes 40 passes to render a picture, this one takes about six, which Viggle reports makes it roughly five times faster from prompt to finished image.

Qwen-Image-2.1 is Qwen's own official demo of its unified text-to-image generation and image-editing model.