寒武纪与摩尔线程完成对GLM-4.6的适配，标志着国产GPU已具备与前沿大模型协同迭代的能力，加速 构建自主可控的AI技术生态。GLM-4.6搭配国产芯片的组合将率先通过智谱MaaS平台面向企业与公众 提供服务，释放更广泛的社会与产业价值。 未来，国产原创的GLM系列大模型与国产芯片的深度协同，将在模型训练和推理环节持续推动性能与 效率的双重优化，构建更加开放、可控、高效的人工智能基础设施。 智谱官方宣布，GLM-4.6已在寒武纪领先的国产AI芯片上实现FP8+Int4混合量化推理部署，这也是首次 在国产芯片上投产的FP8+Int4模型-芯片一体化解决方案。在保持模型精度不变的前提下，该方案大幅 降低了推理成本，为国产芯片本地化运行大模型提供了可行路径和示范意义。 与此同时，摩尔线程基于vLLM推理框架完成了对GLM-4.6的适配，新一代GPU可在原生FP8精度下稳 定运行模型，充分验证了MUSA架构及全功能GPU在生态兼容性和快速适配能力方面的优势。 9月30日，国内大模型领军企业智谱正式发布并开源新一代大模型GLM-4.6，在Agentic Coding等核心能 力上实现大幅跃升。这是继DeepSeek- ...

Core Insights - The domestic large model key enterprise, Zhipu, has officially released and open-sourced its next-generation large model GLM-4.6, achieving significant advancements in core capabilities such as Agentic Coding [1] - This release follows the major technology launches of DeepSeek-V3.2-Exp and Claude Sonnet4.5, marking another significant development in the industry before the National Day holiday [1] - Zhipu announced that GLM-4.6 has been deployed on leading domestic AI chips from Cambrian using FP8+Int4 mixed-precision quantization inference, representing the first production of an FP8+Int4 model-chip integrated solution on domestic chips [1] - Additionally, Moore Threads has completed the adaptation of GLM-4.6 based on the vLLM inference framework, allowing the new generation of GPUs to stably run the model at native FP8 precision [1]

目前，GLM-4.6已在寒武纪国产AI芯片上实现FP8+Int4混合量化推理部署，这也是首次在国产芯片上投 产的FP8+Int4模型-芯片一体化解决方案。摩尔线程基于vLLM推理框架完成了对GLM-4.6的适配，新一 代GPU可在原生FP8精度下稳定运行模型。 9月30日，智谱正式发布并开源新一代大模型GLM-4.6，在Agentic Coding等核心能力上实现较大提升， 代码生成能力对齐Claude Sonnet 4。 ...

Core Insights - The domestic large model company Zhipu has released and open-sourced its next-generation large model GLM-4.6, achieving significant advancements in core capabilities such as Agentic Coding [1] - GLM-4.6's code generation ability has fully aligned with Claude Sonnet 4, making it the strongest coding model in China, while also surpassing DeepSeek-V3.2-Exp in various aspects including long context processing and reasoning capabilities [1] - The model has been deployed on domestic AI chips with an FP8+Int4 mixed-precision inference solution, marking the first instance of such a model-chip integration on domestic chips, significantly reducing inference costs while maintaining model accuracy [1] Industry Developments - 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] - The combination of GLM-4.6 with domestic chips will be offered through the Zhipu MaaS platform, aiming to release broader social and industrial value [2] - The deep collaboration between the domestically developed GLM series large models and domestic chips is expected to continuously enhance performance and efficiency in model training and inference, contributing to a more open, controllable, and efficient AI infrastructure [2]

风险提示及免责条款 据智谱消息，最新的GLM-4.6模型上线，其代码能力比前代GLM-4.5提升27%，在真实编程、长上下文 处理、推理能力等多方面表现优异。GLM-4.6在公开基准测试中达到国内最高水准，并在74个真实编程 任务中超越其他国产模型。智谱官方宣布，GLM-4.6已在寒武纪领先的国产AI芯片上实现FP8+Int4混合 量化推理部署，这也是首次在国产芯片上投产的FP8+Int4模型-芯片一体化解决方案。与此同时，摩尔 线程基于vLLM推理框架完成对GLM-4.6的适配，新一代GPU可在原生FP8精度下稳定运行模型。 市场有风险，投资需谨慎。本文不构成个人投资建议，也未考虑到个别用户特殊的投资目标、财务状况或需要。用户应考虑本文中的任何 意见、观点或结论是否符合其特定状况。据此投资，责任自负。 ...