Large Model

Baidu's self-developed native multimodal basic big model, with excellent multimodal understanding, text generation and logical reasoning capabilities, using a number of advanced technologies, the cost is only 1% of GPT4.5, and plans to be fully open source.

The Tsinghua University team and Qingcheng Jizhi jointly launched an open source large model inference engine, aiming to realize efficient model inference across chip architectures through underlying technological innovations and promote the widespread application of AI technology.

Google launched a new generation of open source AI models with multi-modal, multi-language support and high efficiency and portability, capable of running on a single GPU/TPU for a wide range of application scenarios.

Byte Jump launched a native bilingual image generation model with excellent comprehension and rendering capabilities for a wide range of creative design scenarios.

Alibaba's open-source multimodal large language model uses RLVR technology to achieve emotion recognition and provide an interpretable reasoning process for multiple scenarios.

Alibaba released a high-performance inference model with 32 billion parameters that excels in mathematics and programming for a wide range of application scenarios.

OpenAI's large-scale language model, officially launched on February 28, 2025, is an upgraded version of GPT-4.

Anthropic has released the world's first hybrid reasoning model that demonstrates superior performance and flexibility by being able to flexibly switch between rapid response and deeper reflection based on different needs.

Alibaba's open source multimodal large language model with powerful visual understanding, OCR, video processing and reasoning capabilities, supporting multiple scale versions.

Google DeepMind launches a 100 billion visual language dataset designed to enhance the cultural diversity and multilingualism of AI models.

The third generation of artificial intelligence models developed by Musk's xAI company, with superior computational and reasoning capabilities, can be applied to a variety of fields such as 3D model generation and game production, which is an important innovation in the field of AI.

NetEaseYouDao launched the first 14B lightweight model in China that supports step-by-step reasoning and explanation, designed for educational scenarios, which can help students efficiently understand complex math problems.

Google released a high-performance AI model with strong coding performance and the ability to handle complex cues with a contextual window of 2 million tokens.

The mega-scale Mixture of Experts model introduced by AliCloud's Tongyi Thousand Questions team stands out in the AI field for its excellent performance and wide range of application scenarios.

Developed by the DeepSeek team, it is an efficient visual language model based on a hybrid expert architecture with powerful multimodal understanding and processing capabilities.

Google introduced a new generation of AI models that support multimodal inputs and outputs and natively integrate intelligent tools to provide developers with powerful and flexible assistant functions.

Hangzhou Depth Seeker has launched an efficient open source language model with 67.1 billion parameters, using a hybrid expert architecture that excels at handling math, coding and multilingual tasks.

An AI model developed by Fei-Fei Li's team that achieves superior inference performance at a very low training cost.

OpenAI introduces small AI models with inference capabilities and cost-effective pricing, designed for developers and users to optimize application performance and efficiency.

The large-scale language model with powerful semantic understanding and knowledge reasoning capabilities introduced by KU Xunfei is widely used in many fields such as enterprise services, intelligent hardware, and smart government.

Vivo's self-developed generalized big model matrix contains several self-developed big models covering core scenarios, providing intelligent assistance, dialog bots, and other functions with powerful language understanding and generation capabilities.

Launched by AliCloud, the ultra-large-scale pre-trained language model has powerful natural language processing and comprehension capabilities, and is able to simulate human thinking for tasks such as multi-round conversations and copywriting, and serves a number of industries and scenarios to provide users with intelligent solutions.

Baidu's industrial-grade knowledge-enhancing big models, with industry-leading natural language understanding and generation capabilities, are widely used in all kinds of natural language processing and generation tasks, helping enterprises realize intelligent upgrading.

Rockchip has developed the first non-Transformer architecture generalized natural language model with high performance, low cost, multimodal processing capability and private deployment security.

Westlake HeartStar's self-developed universal big model, which integrates multimodal capabilities and possesses high IQ and EQ, has been widely used in many fields.

The series of large models jointly developed by Tsinghua University and Smart Spectrum AI have powerful multimodal understanding and generation capabilities, and are widely used in natural language processing, code generation and other scenarios.

Based on industrial data and technology, Jingdong has developed an intelligent large model with extensive industry application capabilities, and is committed to providing efficient and intelligent solutions for enterprises.

Shangtang Technology has launched a comprehensive big model system with powerful natural language processing, text-born diagrams and other multimodal capabilities, aiming to provide efficient AI solutions for enterprises.

Kunlun World Wide's self-developed double-gigabyte large language model, with powerful text generation and comprehension capabilities and support for multimodal interaction, is an important innovation in the field of Chinese AI.

Developed by Tencent, the Big Language Model features powerful Chinese authoring capabilities, logical reasoning in complex contexts, and reliable task execution.