Cost difference matters most as cost optimization is the whole point of AI. Time difference (30 min vs 1 hr) is not a deal-breaker. The small precision gap on the first iteration does not matter for 99% of the work that happens in real world.
GLM 5.2 vs. Opus
31–40 of 367 posts
Re: GLM 5.2 vs. Opus
#32GLM-5.2 is quietly becoming the most interesting open model release this year. The coding benchmarks are surprisingly close to frontier models at a fraction of the inference cost.
To me DS 4 is still the most interesting due to much lower costs. Also DS 4 training isn't done yet.
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.
Re: GLM 5.2 vs. Opus
#33> Through an API it costs a fraction of Opus, and you can run it yourself for free if you have the hardware. I haven't been keeping up on hardware costs for state of the art LLM inference, but this remark made me ask myself how many readers of the article would actually be able to run this model on hardware they own. How much would it cost to acquire such a setup?
This framing local LLMs as free is stupid. Basically pay 100+ months worth of API costs up front isn't free in the slightest. And it will be slower than non-local, your hardware will be outdated in 12 months and probably won't be able to run SOTA at anywhere near non-local speed in max 20 months
Re: GLM 5.2 vs. Opus
#34Chinese models optimize for benchmarks and do poorly in real-world tasks
Not my experience at all, I have written about comparing DS4 vs Opus 4.8 on 16 real life work tasks on multiple posts.
Also, every single lab does RL on benchmarks, which is why Opus 4.6 was the last truly great assistant, after it, all models tend to drift into implementation asap.
Re: GLM 5.2 vs. Opus
#35Pretty clearly it's beating Opus at [web dev](https://www.gptbased.com/) - on price, on score.. I mean what else is there?
Re: GLM 5.2 vs. Opus
#36> Through an API it costs a fraction of Opus, and you can run it yourself for free if you have the hardware. I haven't been keeping up on hardware costs for state of the art LLM inference, but this remark made me ask myself how many readers of the article would actually be able to run this model on hardware they own. How much would it cost to acquire such a setup?
Practically nobody.
Re: GLM 5.2 vs. Opus
#37Seeing the results I don't see how the results are even comparable Opus is clearly far superior in most aspects. Smoothness, design, functionality etc.
At the end of the day, the time earned is more important then the cost for big players.
The ability to spawn 10 claude agents and rush a project to outcompete someone is more important for big businesses in my imo. Also the small details that GLM missed would take significant more time to iron out, considering it already took double the time.
I do hope other (open weight) models catch up, but to act like they are anywhere close for me is a bit disingenuous.
Re: GLM 5.2 vs. Opus
#38> Through an API it costs a fraction of Opus, and you can run it yourself for free if you have the hardware. I haven't been keeping up on hardware costs for state of the art LLM inference, but this remark made me ask myself how many readers of the article would actually be able to run this model on hardware they own. How much would it cost to acquire such a setup?
This framing local LLMs as free is stupid. Basically pay 100+ months worth of API costs up front isn't free in the slightest. And it will be slower than non-local, your hardware will be outdated in 12 months and probably won't be able to run SOTA at anywhere near non-local speed in max 20 months
Yeah, it glosses over a gigantic capital expenditure. It's sort of like saying that an open source modern CPU architecture allows you to build your own CPU "for free" (provided that you own and operate a fab).
Re: GLM 5.2 vs. Opus
#39I wonder how much tokens and time where used for the verifying part.
Maybe GLM 5.2 instantly found the "solution" to read the screen pixel by pixel, but it could also have been a major token and time consumer.
Re: GLM 5.2 vs. Opus
#40>On output tokens, GLM-5.2 is less than a fifth the price of Opus. 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.
Is it fair when the one is heavily subsidized and the other one is not? I think it's most fair to compare the plain token pricing that is used by everyone.
Z.ai is also believed to be "subsidised". Its parent company is running at a large loss right now.
Anthropic have claimed they expect their first profitable quarter this year -- they may have bigger margins on their raw API than you realise.