Currently testing M3 for agentic tasks. It works OK and their token plan is very cheap. Highly recommend for claw / hermes type of work.
Tested GLM 5.1 for coding last month and it burned through my tokens a bit too quickly, but it worked well enough.
Spoiler alert: this article just says that GLM 5.2 is better in quality than MiniMax M3, but worse value for money.
From the conclusion, I agree with:
> I wouldn't make either one the top-level coordinator by default.
But I do not agree with the follow-up sentence:
> The best shape is still a frontier coordinator or judge above them: GPT-5.5 or Claude Opus deciding what to delegate, checking the finished work, and rerunning narrow pieces when the answer looks wrong. These models make the worker layer much more serious, not the coordinator layer unnecessary.
For the coordinator or judge above them I would put myself, not a too expensive LLM under the control of an external entity, achieving thus simultaneously higher quality, lower cost and greater security.
There are multiple AI influencers on youtube who can't code 5 lines of python to save their lives. But they do own 3 DGX spark and a stack of maxed out mac minis...
(Not complaining, AI is supposed to be democratic)
You will not be able to keep up with the sheer volume, or alternatively you're never gonna ingest as much information as the LLM, so you're gonna miss out. Input tokens are relatively cheap.
Think of yourself as the CTO, they can't possibly make a judgement call on every detail, but an LLM can, and if you're gonna let an LLM do that, might as well go with frontier, and if you're not gonna let an LLM do that, you're stuck with whatever the lower-tier LLMs provided you with.
That doesn't mean you shouldn't read or judge the code at all, but you're still gonna want to use the LLM as the lever.
Considering how close the models are, the extra free queries may be worth it.
What are "extensible strategy shapes" for those who don't speak LLM?
5.1 was happy to log in to a server that has kubectl access to check out why my k8s isn't doing the k8s thing. 5.2 just straight up says nope can't use those credentials that's unsafe.
Can't say I'm stoked about this handholding trajectory of LLMs. Yes yes security, but you're on a local network and all these VMs will get nuked shortly anyway