The real question is not who can code. It is who stays pleasant after two hours.
Every AI coding tool promises speed. The part that matters in real life is what happens after the novelty wears off. Does it help you keep moving when the task gets messy, the repo gets weird, and the first answer is wrong?
That is where these three tools split apart. GLM Coding Plan is the value play: broad support, a lower-looking starting price, and a public pitch that says it works across many agent and IDE surfaces. Claude Code is the easiest to live with day after day. OpenAI Codex is the conservative pick for teams that already want to stay inside the OpenAI ecosystem.
Why GLM deserves a serious look
GLM is not trying to win by sounding fancy. Its public page is blunt: AI coding for agents and IDEs, with plans from $18/month and support for tools like Claude Code, Codex, Cline, OpenCode and OpenClaw.
That breadth matters. It means GLM is not asking you to rebuild your whole workflow around one vendor-shaped box. If you already have a preferred terminal agent or editor plugin, GLM is trying to slide into that stack instead of forcing a new ritual.
The vendor benchmark image also makes a useful point: GLM-5.3 is not a tiny refresh over GLM-5.2. It is a real step up, especially on tool-use and automation-style tasks. That is the kind of improvement that matters when you are asking the model to edit, inspect, retry and keep going.
Still, the same chart is honest enough to keep expectations grounded. GLM-5.3 is better, but it is not an automatic king. Claude and GPT-class models still lead some of the hardest benchmarks. So the right GLM pitch is not “it beats everything.” It is “it is much better than before, and the value story is now compelling enough to care.”
Why Claude Code still feels like the safest default
Claude Code has the most immediately understandable product story of the three. It reads your codebase, edits files, runs commands and lives where developers already work: terminal, IDE, desktop app and browser.
That sounds simple, but simplicity is a real advantage. A lot of tools feel clever in a demo and annoying on day three. Claude Code usually does the opposite. It does not demand a big explanation. You open it, point it at a repo, and it starts behaving like a serious pair programmer.
The downside is that it is also the least exciting from a price-nerd angle. It is easy to recommend, but not because it is the obvious budget hack. If you want the cleanest daily experience, Claude Code wins. If you want the sharpest cost/value story, GLM has a better argument.
Where OpenAI Codex fits
Codex is the steady middle ground. It is the answer for teams that already bought into OpenAI infrastructure and want the same vendor story carried into coding workflows.
That can sound boring, but boring is good when you are shipping. Codex is the kind of choice that makes sense when a team values predictability, vendor alignment and fewer moving parts over the flashiest possible UI or the cheapest possible entry point.
It is also the least emotionally loud of the three. Claude Code feels polished. GLM feels aggressive on value. Codex feels controlled. For some teams, that is exactly what they want.
What the benchmarks actually say
The two benchmark images tell a pretty consistent story.
First, GLM-5.3 is a genuine upgrade over GLM-5.2. On the vendor’s own snapshots, the jump is large enough that you should not think of it as a cosmetic refresh. It looks more like the model finally crossed into a more credible agentic tier.
Second, benchmark wins are not universal. In the larger performance chart, GLM-5.3 is strong on automation-style and tool-use tests, but Claude/GPT-class models still lead some harder evaluations. In the effort-level chart, Claude Opus 4.8 still sits at the top.
That does not make GLM weak. It just means the most honest conclusion is a practical one: GLM is now good enough to compare seriously, but not so dominant that the conversation ends there.
How to choose
Choose GLM Coding Plan if you care about value, broad compatibility and a model family that has clearly moved up a tier. It is the best story for builders who want to keep costs sane while still getting a modern agentic workflow.
Choose Claude Code if you want the smoothest daily experience. If you are the kind of developer who prefers less setup and more momentum, this is still the easiest recommendation.
Choose OpenAI Codex if your team already standardizes on OpenAI tools and you want the coding workflow to fit that existing stack without drama.
The honest verdict
If I were recommending one tool to a random builder, I would still start with Claude Code because it is the least annoying to use every day. But if budget and flexibility matter, GLM is no longer a side character. The latest benchmark snapshot shows real progress, and the pricing pitch is strong enough that it deserves a real trial.
OpenAI Codex remains a sensible choice, but it feels more like the default inside a vendor ecosystem than the tool people get excited about first.
So the short version is this: Claude Code is the best overall experience, GLM is the strongest value bet, and Codex is the safest stack-aligned option.