@kazani

GLM-4.7: the new open source star! The Takeaway: 👉 GLM-4.7 boosts coding and complex reasoning with enhanced planning mechanisms and consistent multi-turn thinking. 👉 The model shows substantial benchmark gains over GLM-4.6, especially in agentic and tool-use scenarios. 👉 It's fully open source and accessible via APIs, making advanced AI capabilities broadly available to developers. 👉 Practical use cases include smarter coding agents, deeper context understanding, and more robust long-form tasks. The AI world just got a major upgrade: GLM-4.7, Z. ai's newest flagship model, has officially launched with a clear focus on stronger coding, reasoning, and multi-step task performance. At its core, GLM-4.7 builds on the impressive foundation of earlier GLM models by enhancing interleaved thinking, a mechanism that lets the system plan ahead before responding, and adding preserved and turn-level thinking for better consistency over long, complex conversations. These upgrades make it much better at handling tasks that require deep logical steps, like debugging code, maintaining context across turns, or orchestrating actions with external tools. But here's what really makes GLM-4.7 stand out for the AI community: It significantly improves real-world coding metrics and reasoning benchmarks compared to its predecessor, while remaining fully open-source and accessible through APIs and platforms like OpenRouter and PPQai (https://ppq.ai/invite/7852e16b) Imagine an AI that not only writes cleaner, more efficient code, but also keeps the "thought process" behind the scenes more stable and reliable - that's what GLM-4.7 aims to deliver. GLM-4.7 pushes the envelope for open-source models in coding and reasoning tasks, offering powerful capabilities without API lock-in. It strengthens the bridge between research and real-world developer workflows in the AI ecosystem. Sources: https://z.ai/blog/glm-4.7 https://docs.z.ai/guides/llm/glm-4.7

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