Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.5, DeepSeek-R1, GLM-5, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Llava, Phi4, ...) (AAAI 2025).

A Next-Generation Training Engine Built for Ultra-Large MoE Models

This is the official website for TuriX Computer-use-Agent

An open-source implementaion for fine-tuning Qwen-VL series by Alibaba Cloud.

Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.

ComfyUI-QwenVL custom node: Integrates the Qwen-VL series, including Qwen2.5-VL and the latest Qwen3-VL, with GGUF support for advanced multimodal AI in text generation, image understanding, and video analysis.

Run generative AI models in sophgo BM1684X/BM1688

Vesta macOS Distribution - Official releases and downloads.Vesta AI Chat Assistant for macOS - Built with SwiftUI, Swift MLX and Apple Intelligence using Apple's on device model on MacOs Tahoe (MacOS 26). Now with side-by-side Qwen3-VL for vison

Tool to automatically generate text descriptions for images using Ollama vision models (LLaVA, Qwen3-VL, Llama Vision)

A tool to streamline AI image captioning

Use 2 lines to empower absolute time awareness for Qwen2.5VL's MRoPE

Qwen3-VL-2B on the RK3588 NPU

[CVPR 2026] This is the official PyTorch implementation of "MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping".

Simple image and video captioning app with a Gradio UI, powered by Qwen2.5/3 VL Instruct.

This repository is a CUA (computer use agent) system that, using the Qwen3-VL model on Ubuntu computers, aims to perform tasks on your behalf using the keyboard and mouse in a local Sandbox environment in GGUF format, based on the commands you provide.

Qwen-Image-Edit-2509-LoRAs-Fast is a high-performance, user-friendly web application built with Gradio that leverages the advanced Qwen/Qwen-Image-Edit-2509 model from Hugging Face for seamless image editing tasks.

Video object tracking, point tracking, and video question answering using the Qwen3-VL multimodal vision-language model. Supports text-guided detection with bounding box overlays, precise point tracking with motion trails, and open-ended video comprehension through natural language queries.

Qwen3-VL-Outpost is an experimental, high-performance visual reasoning and multimodal inference suite designed for advanced image analysis, optical character recognition, and complex scene understanding. Built around the state-of-the-art Qwen3-VL and Qwen2.5-VL model families.

Multimodal-OCR3 is a highly capable, experimental optical character recognition and visual processing suite designed for precise text extraction, document parsing, and markdown generation. Leveraging a powerful selection of vision-language.

A Gradio-based demonstration for the AllenAI SAGE-MM-Qwen3-VL-4B-SFT_RL multimodal model, specialized in video reasoning tasks. Users upload MP4 videos, provide natural language prompts (e.g., "Describe this video in detail" or custom questions), and receive detailed textual analyses.