How to Code with GLM 5.2 on OpenCode - Petar Djukic
Petar Djukic
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How to Code with GLM 5.2 on OpenCode<br>Coding with GLM 5.2 on OpenCode is a bet on your own engineering. Decide the architecture and interfaces first, let the cheap model write the code on a fixed twenty-dollar Ollama plan, and bring a str
Petar Djukic<br>Jul 09, 2026
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If you want to code with GLM, plan to lean on your own engineering. A cheap model turns decisions into working code, and it turns missing decisions into confident messes. The architecture, the component boundaries, the interfaces between them — those have to exist before the first prompt, because GLM will not supply them. You decide, the model types, and where your trust runs out, a stronger model checks the work.<br>Worked that way, the arrangement pays for itself twice over. My agent — OpenCode driving GLM 5.2 on Ollama Cloud, wrapped in a generate-and-audit loop — does production work for a fixed twenty dollars a month, around twenty-nine Canadian the day I am writing this, and the code it committed last month to a public repository is real, with real tests. A metered frontier agent has no such ceiling; I once instrumented a single session and watched it pass thirty dollars before it finished [1]. The plan caps the bill, and the discipline underneath it is what makes a cheap model safe to point at production code.<br>Why this stack
None of the code depends on Claude the model. What everything depends on is the workflow you build around whatever models you run, and the workflow decides what each model is trusted with.<br>Two separate choices sit underneath. One is the plan you run on, which decides what you pay. The other is the model, which decides what the agent can do.<br>The plan: budget certainty
Ollama Cloud bills by GPU time on a subscription, with session and weekly windows, not by the token [2]. Its shape is close to an Anthropic plan: a fixed monthly price, usage metered against time windows, and a hard stop when you reach them instead of an open invoice. Twenty dollars a month, and the number cannot surprise you.<br>A token-metered provider works the other way. Run the very same GLM model through OpenRouter [5] and you pay per token, with no subscription and no ceiling, so heavy use simply costs more.<br>Vendor pricing keeps drifting toward consumption, and the tools built on top have grown more expensive, not less. A plan fixes your exposure to a number you can read in advance.<br>Context grows as a project does, and on a metered API every extra token costs more on every call. On one pipeline, the gap between caching the project docs and not caching them was thirty-three dollars against a hundred and eighty [1]. On a plan billed by time, that pressure is gone.<br>Currency is the force almost nobody mentions, because almost everybody writing about AI cost is paid in the same dollars they spend. I pay a US-priced plan in Canadian dollars. When the loonie weakens, a metered bill multiplies, because it already scales with usage, while a time-windowed plan barely moves.<br>The model: cheap, made reliable
GLM 5.2 is the model, the current flagship from Z.ai, on Ollama Cloud as glm-5.2 [3]. It costs a fraction of a frontier model and does real production work, on one condition. You run the workflow around it. Left to range over a whole project, a cheaper model keeps each file consistent and drops the connections between them. The loop closes that gap.<br>GLM through a metered provider would still be cheap per token, but with no ceiling. Ollama gives you both: the cheap model and the capped bill.
Figure 1. Two stacks, one workflow. Claude wraps Opus 4.8, a frontier model. OpenCode wraps GLM 5.2, a cheaper model on a flat plan with a fixed one. Underneath, the techniques — self-contained issues, context resets, an audit pass — are what let you move from the expensive stack to the cheap one without losing the work.<br>The setup, in the background
The plumbing takes half an hour and none of it is the interesting part. You need a Git repository for a Go project with git and gh authenticated, an Ollama account on the Pro plan with the glm-5.2 cloud model enabled [2][3], OpenCode, and Claude Code. Two prompts to Claude Code do the wiring. Spend the expensive agent on setup now and keep it for judgment later. First the provider config:<br>Configure OpenCode in this repo to use Ollama Cloud as its model provider.<br>Add a provider entry that points at the Ollama Cloud endpoint, reads my<br>OLLAMA_API_KEY from the environment, and sets glm-5.2 as the default model.<br>Read the current OpenCode configuration docs to get the exact file location<br>and field names right. Show me the diff before you write anything.<br>Then the command set, from coding-skills [4]:<br>From the public repository github.com/petar-djukic/coding-skills, copy<br>the OpenCode command files in .opencode/commands/ — make-work, gh-issue-push,<br>gh-issue-show, gh-issue-pop, do-work — into my OpenCode commands directory, so<br>they load in every...