腾讯混元开源 4 个小尺寸模型，主打 Agent 和长文

Core Viewpoint - Tencent's Hunyuan has announced the open-sourcing of four small-sized models with parameters of 0.5B, 1.8B, 4B, and 7B, which can run on consumer-grade graphics cards and are suitable for low-power scenarios like laptops, smartphones, and smart home devices [2][12]. Model Features - The newly open-sourced models are fusion inference models characterized by fast inference speed and high cost-effectiveness, allowing users to choose between fast and slow thinking modes based on their usage scenarios [4]. - All four models have achieved performance benchmarks comparable to industry standards, particularly excelling in language understanding, mathematics, and reasoning, with leading scores on multiple public test sets [5]. Technical Highlights - The models feature enhanced agent capabilities and long-context abilities, allowing them to handle complex tasks such as deep searches and Excel operations, with a native long context window of 256k, enabling the processing of up to 400,000 Chinese characters or 500,000 English words in one go [10]. - Deployment of these models requires only a single card, and they can be directly integrated into various devices like PCs, smartphones, and tablets, supporting mainstream inference frameworks and multiple quantization formats [10]. Application Scenarios - The models have been practically tested in various Tencent services, demonstrating their usability and practicality. For instance, the Tencent Meeting AI assistant and WeChat Reading AI assistant can understand and process complete meeting content and entire books [11]. - In specific applications, the models have improved spam message recognition accuracy in Tencent Mobile Manager and enhanced user interaction experiences in Tencent Maps through intent classification and reasoning capabilities [11]. Open Source Strategy - Tencent is committed to the long-term direction of open-sourcing its Hunyuan models, continuously enhancing model capabilities and embracing open-source initiatives to accelerate industry application and collaboration with developers and partners [13].