GLM-5.2
GLM-5.2 is a 753B-parameter model you reach through an API — too large to self-host, so this page covers what it does, how to access it, and what to run locally instead.
You don't run GLM-5.2 locally
At 753B parameters, a Q4-class build of GLM-5.2 would need roughly 452 GB — only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom (0.6 GB per billion parameters, our standard Q4 rule). Access is through the hosted API.
Jun 13, 2026 coding-first flagship from Z.ai; MIT weights published on HuggingFace in July 2026 (753B total MoE). Works with Claude Code, Cline and OpenCode via the API. Weights are far beyond consumer hardware; use the API or hosted providers.
Strong local alternatives
More Zhipu models
Frequently asked questions
Can I run GLM-5.2 locally?
Not realistically. GLM-5.2 is a 753B-parameter model; a Q4-class build would need roughly 452 GB — only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom. The hosted API or a smaller open model is the practical path.
How do I access GLM-5.2?
Through the vendor-hosted API. See the official source linked on this page.
What is the best local alternative to GLM-5.2?
Qwen3 235B A22B is the strongest local model we track (235B). It runs on a single high-memory Mac or GPU; see its page for exact hardware.
Cite this page
ModelFit: GLM-5.2 — specs, memory math and hardware verdicts. https://modelfit.io/models/glm-5.2/ (dataset updated 2026-09-03, CC BY 4.0).