After using GLM-5.2 on real code, I would put it in the GPT-5.5 tier for coding-agent work.

This post gives you three things:

My current provider map looks like this.

Cursor is the easiest path if you already pay for it. GLM-5.2 High is free for paid users, and I have not found an official announcement calling this a limited-time offer. While that remains true, usage feels close to unlimited.

Devin is attractive during the free window. GLM-5.2 is free for paid users until July 5, and usage also feels close to unlimited while it remains free. I cannot speak to its vision path because I do not have a paid Devin account to test it.

OpenCode Go is cheap and fast, but its $60 USD/month usage cap changes the feel of long agent runs. It is a good fit when you want GLM-5.2 in OpenCode or when you want to experiment with a low-cost provider across agents.

Ollama Pro/Max is the better fit for heavy users. My observed usage: 412 requests for 87.2 session usage, and 961 requests for 30% weekly usage, which implies about 3,200 requests per week. I built two client-server web apps within 8 hours and spent 15% weekly usage.

I do not recommend bigmodel.cn or z.ai as the default route for this setup. Both of them are run by Zhipu, the lab builds GLM 5.2. bigmodel.cn does not guarantee SLA and requires KYC verification. z.ai is twice as expensive as bigmodel.cn.

Vision is the hard boundary. GLM-5.2 does not see images. The useful question is whether the agent can route the visual part of the task somewhere else.

Cursor handles this best. It auto-routes vision-understanding tasks to a model that supports vision, then lets GLM-5.2 continue the coding work.

I cannot verify Devin's vision support because I do not have a paid Devin account.

ZCode auto-routes vision-understanding tasks when you use a bigmodel.cn or z.ai plan. That path does not work with images through Ollama Pro/Max or OpenCode Go.

In OpenCode, the workaround is to delegate visual tasks to a subagent backed by a vision-capable model. It works, but the handoff is clumsy: the vision subagent does not share state smoothly with browser-use or computer-use MCP sessions. I am building a plugin to make that flow feel native, and I do not know of an open-source alternative yet.

The setup details are mechanical, but the distinction matters: OpenCode Go and Ollama Pro/Max expose different routes. Keep their endpoints separate.

Use OpenCode's native setup:

The official docs describe this path directly. Use it before trying any manual provider file.

Use these values:

Base URL: https://opencode.ai/zen/go/v1

API Format: Chat Completions

Model Name: glm-5.2

Context Window Size: 976000

Use the official launch command:

Use the official launch command:

Use the official launch command:

Use these values:

Base URL: https://ollama.com/v1

API Format: Chat Completions or Responses

Model Name: glm-5.2-cloud

Context Window Size: 976000

If you already pay for Cursor, start there. It gives the best GLM-5.2 experience right now because the model is free for paid users in my account, and the client handles vision routing.

If you work mostly in terminal agents and want a larger context window, Ollama Pro is the practical starting point. If you are a heavy user, Ollama Max is the one that makes sense. Both are fast, both give you a 1M-class context window, and the launch commands remove most setup work.

If you want the cheapest cross-agent subscription, OpenCode Go is still useful, but the $60 USD/month usage cap makes it the least comfortable option for heavy loops.

That is where I land: GLM-5.2 is a strong text-first coding model, and the affordable providers make it practical. Vision remains the boundary. The provider or agent has to supply the eyes.