GLM-4.7-Flash

The Hacker News thread on GLM-4.7-Flash (378 points, 135 comments, submitted by scrlk) captures community testing of the model in OpenCode running local 30B-A3B quantizations via llama.cpp on a 32 GB GPU with 128k context. One commenter reports that Qwen3-Coder had previously given the best results in their workflow of Early user issues documented in the thread include broken tool calling in OpenCode, rapid self-repetition (mitigated by raising llama.cpp's --dry-multiplier to 1.1 or higher), and spelling errors such as class or file-name characters being replaced with "1" or "AGENTS.md" being misread as "AGANTS.md". A later reply ann

AIbase reports that Zhipu AI officially open-sourced GLM-4.7-Flash in the early hours of January 20, 2026, framing it as a "Hybrid Thinking" model and the strongest competitor in the 30B specification class. The article confirms the 30B-A3B MoE design, where approximately 3 billion of 30 billion parameters activate per The excerpt lists the same vendor-published benchmark scores: 59.2 on SWE-bench Verified for code repair, 91.6 on AIME25 and 75.2 on GPQA for math and expert-level reasoning, 79.5 on τ²-Bench and 42.8 on BrowseComp for tool collaboration and agent scenarios. These figures are reported as surpassing Alibaba's Qwen3-30B-