Today, the Alibaba Cloud Tongyi team officially released the new mathematical reasoning process reward model Qwen2.5-Math-PRM. This model offers two sizes, 72B and 7B, with performance significantly outperforming similar open-source process reward models, especially excelling in identifying reasoning errors. The 7B version of Qwen2.5-Math-PRM astonishingly surpasses the widely popular GPT-4o, marking an important step in Alibaba Cloud's research and development of reasoning models.

Recently, Alibaba Damo Academy launched a multi-modal large language model named Valley 2, designed for e-commerce scenarios. It aims to enhance performance across various fields and expand the application boundaries of e-commerce and short video scenarios through a scalable vision-language architecture. Valley 2 utilizes Qwen 2.5 as its LLM backbone, paired with the SigLIP-384 visual encoder, incorporating MLP layers and convolution for efficient feature transformation.

The Qwen team recently announced the open-source release of their latest multimodal reasoning model, QVQ, marking an important step forward in the capabilities of artificial intelligence in visual understanding and complex problem-solving. This model is based on Qwen2-VL-72B and aims to enhance AI reasoning capabilities by combining language and visual information. In the MMMU evaluation, QVQ achieved a high score of 70.3, demonstrating significant performance improvements over Qwen2-VL-72B-Instruct in several math-related benchmark tests.

The Alibaba Cloud Bairen Model Service Platform recently launched the 'Real-Time Audio and Video Interaction' feature, enabling users to easily build multi-modal AI applications without the need for programming knowledge. This new feature allows users to quickly integrate AI models into Web, iOS, and Android applications and share them with others. Users can create intelligent agent applications through simple steps: first, create a new intelligent agent application, then select and configure the required text, speech, or visual understanding models on the Alibaba Cloud Bairen platform. The platform offers over 200 large models, including

Recently, Alibaba announced the open sourcing of its latest image generation model, Qwen2vl-Flux. This model not only features a variety of functionalities such as editing, fusion, and mixing, but it can also generate highly similar new images based on user-input images or text. Qwen2vl-Flux provides powerful image transformation capabilities. Users simply need to input an image without any text prompts, and the model can generate multiple similar images based on the original. For example, if a user uploads a portrait photo, the model can generate multiple angles.

The Aliyun Bailing platform recently announced the launch of the Qwen2.5-Turbo million long text model, developed by the Tongyi Qianwen team. The Qwen2.5-Turbo model supports processing ultra-long contexts of up to 1 million tokens, equivalent to 1 million English words or 1.5 million Chinese characters.

The Tongyi Qianwen team recently announced the open sourcing of their latest Qwen2.5-Coder full series, aimed at promoting the development of Open Code LLMs. Qwen2.5-Coder has garnered attention for its power, diversity, and practicality. The Qwen2.5-Coder-32B-Instruct model has achieved SOTA levels in coding capabilities, comparable to GPT-4o, demonstrating comprehensive abilities.

Recently, an open source multimodal AI model named Molmo has drawn widespread attention in the industry. This AI system, based on Qwen2-72B and leveraging OpenAI's CLIP as the visual processing engine, is challenging the dominance of traditional commercial models with its outstanding performance and innovative features. Molmo's standout characteristic is its efficient performance. Despite its relatively small size, it can compete with competitors that are ten times larger in processing capability. This 'small but exquisite' design philosophy not only enhances the model's

The 2024 Yunqi Conference opened grandly in Hangzhou, with Alibaba Group CEO and Alibaba Cloud Intelligence Group Chairman and CEO Wu Yongming delivering a keynote speech. During the conference, Alibaba announced a series of groundbreaking releases, including the launch of the next-generation open-source model Qwen2.5, which outperforms Llama405B and firmly holds the position of the 'strongest open-source large model'.

The Tongyi Qianwen team announced the official open source of the latest member of the Qwen family, the Qwen2.5 series language models, three months after the Qwen2 release. This marks one of the largest open source releases in history, including the general language model Qwen2.5, as well as the Qwen2.5-Coder and Qwen2.5-Math models specifically designed for programming and mathematics.

Alibaba Group's Tongyi Qwen QwenLM project has encountered an unexpected takedown of its Github page, resulting in a 404 error message when users try to access it. Project leader Lin Junyang responded in a social media post, stating that the team has not disappeared and is in communication with officials to resolve the page takedown issue. Despite the team's efforts, the page remains inaccessible. It is worth noting that the team recently released the Qwen2-VL model, which has excelled in processing video content up to 20 minutes long, surpassing multiple authoritative evaluation metrics for multimodal models, with some metrics even exceeding those of GPT.

On September 2nd, Tongyi Qwen announced the open sourcing of its second-generation visual language model Qwen2-VL, and launched APIs for the 2B and 7B sizes as well as their quantized versions on the Aliyun Bailian platform for direct user access. The Qwen2-VL model achieves comprehensive performance improvements in several areas. It can understand images of different resolutions and aspect ratios, setting global leading performance on benchmarks such as DocVQA, RealWorldQA, and MTVQA.

Alibaba's cloud computing division has released the new AI model Qwen2-VL, which possesses strong capabilities to understand visual content. It can analyze videos lasting up to 20 minutes in real-time, summarize the video content, answer related questions, and provide online chat support. In third-party benchmark tests, Qwen2-VL surpassed several metrics including Meta's Llama 3.1, OpenAI's GPT-4o, Anthropic's Claude 3 Haiku, and Google's Gemini 1.5 Flash.

On August 30, 2024, Alibaba Damo Academy's Tongyi Qianwen team announced a significant update to its latest achievement—the Qwen2-VL model. The Qwen2-VL model has achieved remarkable improvements in image understanding, video processing, and multilingual support, setting new benchmarks for key performance indicators.

Alibaba's Tongyi Qianwen team has released a math model named Qwen2 Math Demo, which excels at processing mathematical problems in text input and formulas in images and screenshots. It even surpasses GPT-4 on the MATH dataset, improving the score by 9.6%. The model has three versions, with the 72B version being particularly outstanding, outshining GPT-4 in challenging math problems and also outperforming Llama-3.1 on classic test sets like GSM8K and MATH.