Core Viewpoint - The release of the new open-source Agent base model Step3.5Flash by Jumpsky is aimed at real-time Agent workflow scenarios, utilizing a sparse MoE architecture with a total parameter count of 196 billion, balancing inference speed and cost [1] Group 1: Model Specifications - Step3.5Flash achieves an inference speed of up to 350 tokens per second for single request code tasks [1] - The model activates approximately 11 billion parameters per token [1] Group 2: Industry Collaboration - Multiple chip manufacturers, including Huawei Ascend, Muxi Co., Biran Technology, and Suiruan Technology, have completed adaptations for the Step3.5Flash model [1] - Jumpsky previously initiated the "MoCore Ecological Innovation Alliance" in July 2025 with several chip and infrastructure manufacturers to enhance computing efficiency and promote the application of large models [1] - The model release is seen as a further practice in the direction of model and computing power collaboration [1]

Core Insights - The core focus of the news is the launch of the new open-source Agent base model, Step 3.5 Flash, by Jiyue Xingchen, which is designed for real-time Agent workflow scenarios, balancing inference speed, intelligence level, and cost efficiency [1][3] Model Performance - Step 3.5 Flash achieves a maximum inference speed of 350 tokens per second for single request code tasks [1][3] - The model utilizes a sparse MoE architecture, activating approximately 11 billion parameters per token out of a total of 196 billion parameters, significantly enhancing inference efficiency while maintaining model capability [1][3] Industry Collaboration - Jiyue Xingchen has collaborated with several chip manufacturers, including Huawei Ascend, Muxi Co., Birun Technology, Suiyuan Technology, Tianshu Zhixin, and Alibaba Pingtouge, to adapt Step 3.5 Flash, enhancing model adaptability and computational efficiency [1][3] - The collaboration aims to lower inference costs and reduce the overall barriers for enterprises and developers in applying large models, accelerating the practical application of large models in various scenarios [1][3] Ecosystem Development - In July 2025, Jiyue Xingchen initiated the "MoCore Ecological Innovation Alliance" with nearly 10 chip and infrastructure manufacturers to bridge the technical barriers between chips, models, and platforms [2][4] - The alliance aims to optimize and enhance computational efficiency, facilitating the large-scale application of models across various industry scenarios [2][4] - The industry recognizes that deep collaboration between models and computational resources will be a crucial path for promoting the large-scale application of inference models [2][4]