Wan2.2 is a major upgrade version of the basic video model, focusing on integrating innovative technologies such as effective MoE architecture, efficient training strategies, and multimodal fusion into the video diffusion model, bringing more powerful and efficient solutions to the field of video generation.

MultimodalDiffusersMultiple Languages

This repository contains a 4-step distilled model optimized for HunyuanVideo-1.5, which can achieve ultra-fast 4-step inference without using CFG (Classifier-Free Guidance), significantly reducing the generation time while maintaining high-quality video output.

MultimodalDiffusers

The quantized GGUF version of Tencent's Hunyuan Video 1.5 model, specifically designed for text-to-video generation tasks, supports 720P HD video generation, and offers multiple quantization precision versions to optimize usage efficiency.

MultimodalGguf

This project provides a quantized GGUF version of Tencent's Hunyuan Video 1.5 text-to-video model, which supports 480P video generation tasks. It includes both distilled and full models and can be used in conjunction with tools such as ComfyUI-GGUF.

MultimodalGguf

This project provides a quantized GGUF version of the Tencent HunyuanVideo-1.5-I2V-720p model, specifically designed for image-to-video and video generation tasks. The model supports converting static images into high-quality video content and offers multiple quantized versions to optimize performance.

MultimodalGguf

The quantized GGUF version of Tencent's Hunyuan Video 1.5 model, specifically designed for image-to-video and video generation tasks. It offers distilled and standard models with a 480P resolution and supports multiple quantization precisions, including Q4_K_S, Q8_0, and FP16, etc.

MultimodalGguf

A quantized model optimized for HunyuanVideo-1.5, used in conjunction with the LightX2V framework, which significantly reduces memory usage while maintaining high-quality video generation performance.

MultimodalDiffusers

The first truly open-source and unrestricted anime video generation model, based on the Wan2.2-5B architecture, can run with only 6GB of video memory and can generate amazing anime animation content.

MultimodalDiffusers

ChronoEdit-14B is an image editing and world simulation model with temporal reasoning capabilities developed by NVIDIA, with 14 billion parameters. It achieves physically-aware image editing and action-conditioned world simulation through a two-stage reasoning process, extracting prior knowledge from pre-trained video generation models.

MultimodalDiffusersMultiple Languages

Hunyuan Video-1.5 is a lightweight and high-performance video generation model. With only 8.3 billion parameters, it can provide top-notch video quality, significantly lowering the usage threshold. It can run smoothly on consumer-grade GPUs, supporting text-to-video and image-to-video generation, enabling every developer and creator to use it easily.

MultimodalDiffusersMultiple Languages

SAM 3 is the third - generation promptable segmentation foundation model launched by Meta. It can use text or visual prompts (points, boxes, masks) to detect, segment, and track objects in images and videos. Compared with previous generations, SAM 3 introduces the ability to exhaustively segment all instances of open - vocabulary concepts, supports a large number of open - vocabulary prompts, and achieves 75 - 80% of human performance on the SA - CO benchmark.

Computer VisionTransformersEnglish

Qwen3-VL-4B-Instruct is the latest vision-language model in the Tongyi Qianwen series. It achieves excellent visual perception, text understanding and generation, spatial reasoning, and intelligent agent interaction capabilities at the 4B parameter scale. It supports long contexts and video understanding, and has powerful OCR and multi-language processing capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

Qwen3-VL-32B-Thinking is the most powerful vision-language model in the Qwen series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context processing, spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL-8B-Thinking is the most powerful vision-language model in the Tongyi Qianwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in - depth visual perception and reasoning capabilities, long - context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision - language model in the Tongyi series, with comprehensive upgrades in text understanding and generation, visual perception and reasoning, context length, spatial and video dynamic understanding, and agent interaction capabilities. This model offers both dense architecture and mixture - of - experts architecture, supporting flexible deployment from edge devices to the cloud.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series, achieving comprehensive upgrades in all aspects, including excellent text understanding and generation capabilities, deeper visual perception and reasoning capabilities, longer context length, enhanced spatial and video dynamic understanding capabilities, and stronger agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities. This version is a thinking-enhanced version with 2B parameters, specifically optimized for reasoning capabilities.

MultimodalTransformers