GLM-5.2 — Zhipu AI (Z.ai) 的本地 AI 模型
作者： Jakub Rusinowski · 最后更新：
Z.ai's June 2026 flagship and, by Artificial Analysis' ranking at the time, the strongest open-weight model available — fourth overall including closed models. A 744B-parameter Mixture-of-Experts with roughly 40B active per token and a genuinely usable 1M-token input context (output up to 131,072). Two selectable reasoning-effort levels. Released in stages between 13 and 17 June 2026: the Coding Plan first, then open weights on Hugging Face, then documentation. The MIT license is the notable part — full commercial use, modification and redistribution on a frontier-scale model.
变体
GLM-5.2 最小的变体在 Q4_K_M 下约需 450 GB 显存——量化权重加框架开销，不含 KV 缓存。
| 模型 | Q4 下显存 | 显存 | 上下文 | 运行 |
|---|---|---|---|---|
| GLM-5.2 744B → 744B (~40B active) | ~450 GB | 1,000,000 | ollama run glm-5-2 |
显存为 Q4_K_M 下的量化权重加开销，与 GPU 与显存检测器使用同一引擎计算。
如何在本地运行 GLM-5.2
安装 Ollama，然后拉取标签。
ollama run glm-5-2在上方选择一个尺寸，查看它自己的显存、速度估算和安装命令。
许可证
Commercial use permitted. No usage restrictions beyond attribution.
适用于: GLM-5.2 744B推荐 GPU
目录中能在本地运行 GLM-5.2（至少 450 GB 显存）的最便宜 GPU 是 Apple M3 Ultra (512 GB).
我的 GPU 能运行 GLM-5.2 吗？
GLM-5.2 — 常见问题
How much VRAM does GLM-5.2 need?
GLM-5.2 needs about 450 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: GLM-5.2 744B (450 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run GLM-5.2 on an RTX 4090 (24 GB)?
GLM-5.2's smallest variant needs about 450 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.
What quantization should I use for GLM-5.2?
Q4_K_M is the best balance of quality and VRAM for GLM-5.2 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run GLM-5.2 with Ollama?
GLM-5.2 has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.