智谱正式发布并开源新一代大模型GLM-4.6 寒武纪、摩尔线程完成对智谱GLM-4.6的适配

Core Insights - The release of GLM-4.6 by Zhipu marks a significant advancement in large model capabilities, particularly in Agentic Coding and other core functionalities [1] - GLM-4.6 has achieved comprehensive alignment with Claude Sonnet4 in code generation, establishing itself as the strongest coding model in China [1] - The model has undergone extensive upgrades in long context processing, reasoning, information retrieval, text generation, and agent applications, surpassing the performance of DeepSeek-V3.2-Exp [1] - As an open-source model, GLM-4.6 is one of the strongest general-purpose large models globally, enhancing the position of domestic large models in the global competitive landscape [1] Technological Developments - Zhipu has implemented FP8+Int4 mixed-precision quantization inference deployment on leading domestic AI chips from Cambrian, marking the first production of an FP8+Int4 model-chip integrated solution on domestic chips [1] - This solution significantly reduces inference costs while maintaining model accuracy, providing a feasible path for local operation of large models on domestic chips [1] - Moore Threads has adapted GLM-4.6 based on the vLLM inference framework, demonstrating the advantages of the MUSA architecture and full-featured GPUs in ecological compatibility and rapid adaptation [2] Industry Implications - The collaboration between Cambrian and Moore Threads signifies that domestic GPUs are now capable of iterating in synergy with cutting-edge large models, accelerating the construction of a self-controlled AI technology ecosystem [2] - The combination of GLM-4.6 and domestic chips will initially be offered to enterprises and the public through the Zhipu MaaS platform, unlocking broader social and industrial value [2] - The deep collaboration between domestically developed GLM series large models and domestic chips will continue to drive dual optimization of performance and efficiency in model training and inference, fostering a more open, controllable, and efficient AI infrastructure [2]