IBM has released Granite 3.2, a smaller AI model designed for efficient inference and practical applications. This release focuses on delivering strong performance with reduced computational resources.

Alibaba has open-sourced its new inference model, Tongyi Qianwen QwQ-32B, enabling users with consumer-grade GPUs to achieve surprisingly high performance. This makes advanced AI capabilities accessible to a wider audience.

Alibaba has open-sourced a new inference large language model, QwQ-32B. Benchmarks show performance comparable to DeepSeek-R1, but with significantly reduced VRAM requirements.

Tongyi Lingma has announced the launch of its latest inference model, Qwen2.5-Max, offering developers powerful programming and mathematical capabilities. Trained on over 20 trillion tokens and incorporating a meticulously designed post-training scheme, Qwen2.5-Max demonstrates exceptional performance.

DeepSeek launched an official account on Zhihu and published a technical article, "DeepSeek-V3/R1 Inference System Overview," detailing its model inference system optimization and cost-profit margin information for the first time, marking the end of the highly anticipated DeepSeek Open Source Week. The article highlights two key optimization goals for the DeepSeek-V3/R1 inference system: higher throughput and lower latency. To achieve these goals, DeepSeek employs large-scale cross-node expert parallelism (EP) technology, although...

ByteDance's Trae, an AI-powered programming software, has integrated Claude 3.7, offering developers a powerful and free-to-use tool. This integration is expected to significantly enhance coding efficiency and productivity.

On February 25th, Anthropic officially released its latest reasoning model - Claude 3.7 Sonnet. This model, with its innovative design and significantly improved programming capabilities, quickly became an industry focus. The core innovation of Claude 3.7 Sonnet lies in its fusion of rapid response and in-depth reasoning capabilities, simulating human thought processes to provide users with a more seamless interactive experience.

Anthropic, an AI company, today announced the release of its latest hybrid reasoning model, Claude 3.7 Sonnet. Anthropic claims this model is its most intelligent AI yet, designed to tackle more complex problems and demonstrating superior performance in areas such as mathematics and coding.

In the field of artificial intelligence, the DeepSeek team recently released their latest research成果, introducing an innovative sparse attention mechanism named NSA (Native Sparse Attention). The core objective of this technology is to enhance the speed of long context training and inference, particularly optimized for modern hardware, significantly improving the efficiency of training and inference. The launch of NSA technology brings significant changes to the training of artificial intelligence models. Firstly, it utilizes a series of advancements tailored for modern computational hardware.

The ByteDance Doubao large model team announced today the successful development of a new sparse model architecture called UltraMem. This architecture effectively addresses the high memory access issues during the inference of MoE (Mixture of Experts) models, improving inference speed by 2 to 6 times compared to MoE, and reducing inference costs by up to 83%. This groundbreaking advancement opens a new path for efficient inference of large models. The UltraMem architecture successfully resolves the memory bottleneck during inference of MoE architectures while maintaining model performance. Experimental results show that the parameters and activation conditions are the same.

Today, the iFlytek Open Platform officially launched the 807th AI capability – the full series of DeepSeek models, provided by Hangzhou DeepSeek. The full series includes two versions: DeepSeek-V3 and DeepSeek-R1, both supporting public cloud API calls and one-click deployment of dedicated models. Notably, the iFlytek Open Platform also introduced the DeepSeek large model fine-tuning service, allowing developers to deeply customize 'smarter and more suitable' solutions based on business scenario data.

OpenAI recently announced the detailed inference process of its latest inference model, o3-mini, which is seen as a response to the increasing pressure from competitors like DeepSeek-R1. This change marks a significant shift in OpenAI's strategy towards model transparency. Previously, OpenAI regarded the 'Chain of Thought' (CoT) as a core competitive advantage and chose to keep it concealed. However, with open models like DeepSeek-R1 fully showing their inference paths, this has led to a reevaluation.

On January 22, 2025, NetEase Youdao officially released the first inference model in China that supports step-by-step explanations, 'ZiYue - o1'. This model features a design with 14 billion parameters, enabling efficient deployment on standard consumer-grade graphics cards, marking a significant advancement in the application of artificial intelligence technologies in the domestic education sector. 'ZiYue - o1' utilizes Thinking Chain technology and incorporates self-dialogue and error-correction mechanisms, allowing it to output detailed thinking processes when solving problems. This way, students not only receive answers but also understand the logic behind problem-solving.