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GLM 4.7 Blog

GLM-5 vs GLM-4.7: what changed, what matters, and should you upgrade?

GLM-5 vs GLM-4.7: what changed, what matters, and should you upgrade?

GLM-5, released February 11, 2026 by Zhipu AI (Z.ai), represents a large architectural leap from GLM-4.7: bigger MoE scale (≈744B vs ~355B total params), higher active parameter capacity, lower measured hallucination, and clear gains on agentic and coding benchmarks — at a cost in inference complexity and (sometimes) latency.

How to Use GLM-4.7-Flash Locally?

How to Use GLM-4.7-Flash Locally?

GLM-4.7-Flash is a lightweight, high-performance 30B A3B MoE member of the GLM-4.7 family designed to enable local and low-cost deployment for coding, agentic workflows and general reasoning. You can run it locally three practical ways: (1) via Ollama (easy, managed local runtime), (2) via Hugging Face / Transformers / vLLM / SGLang (GPU-first server deployment), or (3) via GGUF + llama.cpp / llama-cpp-python (CPU/edge friendly).

GLM-4.7 Released: What Does This Mean for AI Intelligence?

GLM-4.7 Released: What Does This Mean for AI Intelligence?

On December 22, 2025, Zhipu AI (Z.ai) officially released GLM-4.7, the newest iteration in its General Language Model (GLM) family — drawing global attention in the world of open-source AI models. This model not only advances capabilities in coding and reasoning tasks, but also challenges the dominance of proprietary models like GPT-5.2 and Claude Sonnet 4.5 in key benchmarks.