Yes, in terms of API pricing, GLM 5.2 outperforms the competition. But the only people that use API billing for their coding work are large corporations, where these highly subsidized subscriptions are being fazed out.
At the same time, none of these companies will use a Chinese API for their employees.
For individuals and smaller teams, Z.ai's coding subscription is outperformed by Anthropic and OpenAI. You probably get around the same usage with Claude, but Codex definitely offers more usage for the amount you pay.
We can have a debate how much Z.ai closed the gap to GPT5.5 and Opus 4.8, but if I can freely decide between them in a world where they all cost the same, I simply wouldn't choose GLM.
So the important question becomes: How good will the offering from Z.ai get with GLM 5.3 or 6 and how much will OpenAI and Anthropic cripple their current offering in the near future.
Employees and students used to coding with thousands of dollars worth of tokens (on a 20/100 dollar plan) will push enterprise to spend.
Having a Chinese model that is competitive won't displace this enterprise spend. But an open model hosted in the US/EU might.
The existence of GLM 5.2 puts a ceiling on how much OpenAI/Anthropic can charge for API Access.
Except there is no evidence of this at all, just people comparing API and subscription pricing. The leaked financial info for OpenAI shows inference is profitable right now, though it does not show a distinction between subscription and API revenue... but if subscription revenue was so lossy, it would hard for total inference to still be profitable.
I believe this is the reason why we can even have this debate. Without this kind of competition we would not have these subsidies.
I just think that as of today, most people will not find a good reason to switch to GLM.
If the world needs any more evidence of Europe's short-sightedness, it would be them running to China to spite the US (instead of creating fertile grounds for their own tech).
It's annoying that the plans are so restrictive beyond usage limits. Understandable maybe, but annoying. In practice, only Anthropic (and maybe Google) are really restrictive though. They really scared me away with their policy of charging API rates after the fact if they consider your usage not TOS-aligned. This might be an ungrounded fear that I have, but I feel this is something they'd do so they scared me away.
As well as people using 3rd party harnesses like OpenCode.
> At the same time, none of these companies will use a Chinese API for their employees
So who are Amazon Bedrock (who serve GLM) targetting?
Individuals are presumably going with one of the cheaper US providers such as DeepInfra ($0.18/M cached input for GLM vs $0.50 for Opus) or Fireworks AI.
A company can buy a NVIDIA B300 and serve it's developers in house with unlimited tokens.
nice try but you intentionally ignored the entire Chinese market & Chinese big corporates. there are 130 Chinese companies in the fortune 500 list, with an average revenue of 80 billion USD each. do you think they are going to sign up for Claude, Codex or GLM? now consider South East Asia, Africa, Middle East, Middle Asia and South America, tell me why their large corporates won't be using GLM API billings?
your western centric view of the world is totally out of date, like it or not, 2026 is vastly different from 1996, the US no longer controls high tech whatsoever.
This implies Opus was potentially much (?) better value.
GLM cost a quarter but Opus was twice as fast. So we are already at GLM actually costing half when you compare on time, without even considering the extra effort and time it would take to get Opus-par results.
It's good to have cheaper options and very impressive to see the Chinese continue to set open standards in this field, but the article is maybe a little over-generous.
For people who follow open LLMs, none of these were quiet and all were the most interesting open model release for a few days/weeks. In one or two months, it will be some other model again. Now I do appreciate the real rapid improvements in open models. But there's also a ton of hype and fast-fashion around all of this.
GLM passes a meaningful threshold of reliability/utility that puts it in a different category for real work. Just like Opus really took off after passing a threshold with 4.5. It's the first open model to do that.
I once gave Sonnet 4.6 and Qwen 3.6 the same real-world task to compare: "extend the existing code with this new requirement". Qwen3.6-27b perfectly followed the existing conventions, while Sonnet 4.6 invented its own conventions that were rejected during CR by another dev (i.e. he basically chose Qwen3.6's output in a blind test). Qwen3.6-27b, run locally, also managed to finish faster on that task (mostly because Sonnet 4.6 made tool calling errors and removed some code by accident, so it spent additional time reverting its errors, and got somewhat confused in the process).
We already have production code running live that was written entirely by Qwen3.6-27b. Although, we plan to move to self-hosting GLM5.2 because it's more versatile.
And there are valid reasons to run local, even if performance (quality and speed) aren't best.
From my Opus vs DS 4 Pro personal benchmarks, 16 different real-life work tasks, DS 4 has performed as well as Opus 4.8 high overall but with few drawbacks:
- on the 16 tasks, one needed several prompts to be steered back into the topic
- its review capabilities seem much worse
- DS4 had the cleanly better solution in 3 cases out of 16, with Opus "only" doing cleanly better 2 times out of 16. But still, I want to emphasize, is the worst case scenarios that imho matter the most, not the best ones, and on that front Opus outperformed.
That being said I spent less than 2$ of API working 4 days, which is more or less what I would've spent with Anthropic APIs for less than one task.
Opus is most expensive model in pay as you go model, but IMO fair comparison should include subscription price as well. For example when one has $100 Claude Max and use it up through the month, it might not be more expensive than GLM, or at least not 5x.
And z.ai themselves also have subscriptions.
I’m currently trying to figure out whether a downgrade from Max 5x to Pro in combination with one of those would save me money and if so, how much.
Edit: seems like Anthropic Pro + GLM Pro (Yearly) would let me almost halve my costs of Anthropic Max 5x. Only concerns are about GLM 5.2 not having vision support and also being kinda slower and also not being as good as Opus.
I think it's most fair to compare the plain token pricing that is used by everyone.
As a consumer, yes, it's totally fair. All that matters to me is the price I pay at the pump, not whether that price is "real" or not.
Anthropic have claimed they expect their first profitable quarter this year -- they may have bigger margins on their raw API than you realise.
I'm saying that this is not necessarily the case. They do a lot of optimisation and don't have the same price pressure to lower margins. They may not be losing as much on subscriptions as people think.
Glm game was completely broken Opus game was at first glance ok but also with bugs
Different models with different cost produced different non perfect results . How is it “close” ? :)
Also on costs : glm burns more tokens on average vs opus . Gpt5.5 burns less surprisingly