🎮️ Github Repository | 🤗 Huggingface Model Collection | 📙 Technical Report
## News - [2026/05/05] 🔥🔥🔥 We have released the technical report of Valley3! Check out the full paper here: [Valley3 Technical Report](https://arxiv.org/abs/2605.01278). - [2026/05/01] 🔥🔥🔥 We have released the model weights of [Valley3](https://huggingface.co/collections/bytedance-research/valley), which is an omni foundation model collection for unified e-commerce understanding and reasoning. - [2025/11/27] 🔥🔥 We have released the technical report of Valley2.5! Check out the full paper here: [Valley2.5 Technical Report](https://raw.githubusercontent.com/bytedance/Valley/refs/heads/main/docs/Valley2_5_Tech_Report.pdf). - [2025/10/26] 🔥🔥 We have released the weights of [Valley2.5](https://huggingface.co/bytedance-research/Valley2.5), which significantly enhances multimodal understanding and reasoning capabilities. It has achieved 74.3 on the OpenCompass Multi-modal Academic Leaderboard! ## Introduction Valley is a cutting-edge multimodal large model designed to handle a variety of tasks involving text, images, and video data, which is developed by ByteDance. Our model: - Achieved the best results in the inhouse e-commerce and short-video benchmarks, much better then other SOTA opensource models. - Demonstrated comparatively outstanding performance in the OpenCompass Benchmark. ## Valley3 Valley3 is built upon the Qwen3-VL backbone and extends it with audio transformer for audio encoding. The audio embeddings are aligned to the visual-language backbone via an MLP-based connector, then concatenated with visual and text tokens into a unified input space, enabling omni-modal understanding.
## Environment Setup & Inference Demo Please refer to the detailed instruction in [Github: Valley3](https://github.com/bytedance/Valley/tree/main/valley3) repository.