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Zhipu GLM

Dynamics of Zhipu's GLM series models: Flagship open-source release, iterative code and reasoning capabilities, tracking of commercialization and ecological progress.

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31 Oct, 01:08Updated
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Oct 31Sat1–3
  1. QbitAI78

    FaceWall AI's ForgeKernel live stream generated an operator from scratch, 9.8% faster than DeepSeek FlashMLA and announced open-source.

    FaceWall AI's operator generation system ForgeKernel generated the DeepSeek-V4.1 FlashMLA Prefill operator from scratch on an NVIDIA B200, with a final time of 472 microseconds, 9.8% faster than FlashMLA's 518 microseconds. The entire process took 22.5 hours, 42 iterations, and 32 versions, using 1 B200 and 22 GPU hours.

    Why it matters: The original provided live stream iteration data and Ascend 3 benchmark results can be used to judge the path of operator generation shifting from manual tuning to intelligent agent self-evolution.

Oct 30Fri
  1. Epoch AI88

    Epoch AI: GLM 5.3 can break multiple Firefox versions during the patch window period.

    Epoch AI's experiment shows that the open-source weight model GLM 5.3 released by Z.ai in August can autonomously construct web attacks targeting six Firefox versions released between September 17 and October 26, exploiting publicly available but not yet pushed security fixes, where visiting the web page causes local files to be read and transmitted.

    Why it matters: Epoch AI replicates patch window attacks using open-source weight models, providing a cost level of about 1000 US dollars per version, available for evaluating the security boundaries of open models.

Oct 24Sat
  1. vLLM Blog62

    vLLM provides an in-depth explanation of the optimization of PCP, DCP, and Hybrid HiSparse for GLM-5.3 on 16 H200s

    vLLM team releases the second part of GLM-5.3 optimization, deploying on 16 H200s with 1 pre-filled node and 1 decoding node, using PCP to split pre-fill by token and DCP to split KV cache by token, allowing 1M context to fit into the pre-fill node

    Why it matters: The vLLM team has dissected how PCP, DCP, and Hybrid HiSparse can be combined on 16 H200s, allowing readers to understand the memory and pre-fetch bottlenecks of long-context deployment.

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