All software benchmark are bullshit currently because none mesure capacity of doing same tasks after 1000 first warmed commit of random stuff. It's always easier to build something from scratch but nobody rebuild their feature from 0 every day.
MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
11–20 of 21 posts
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#12>I'm comfortable calling MiniMax the more eager model in this set because that claim is backed by the artifacts, not by vibe. It repeatedly reached for locks, persistence, policy objects, fallback paths, decorators, and extensible strategy shapes
What are "extensible strategy shapes" for those who don't speak LLM?
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#13The comparison results seem very plausible. 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…
> For the coordinator or judge above them I would put myself
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.
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#14Since I quit my Claude subscription, every month I spend $20 (the cost of CC pro plan) playing around with new models and new providers. 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.
I've been testing M3 for agentic tasks on Hermes and it just gets way too confused. I have really poor result from it compared to GPT-5.4 mini/regular or GLM-5.2 (and even 5.1).
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#15Since I quit my Claude subscription, every month I spend $20 (the cost of CC pro plan) playing around with new models and new providers. 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.
I've been testing M3 for agentic tasks on Hermes and it just gets way too confused. I have really poor result from it compared to GPT-5.4 mini/regular or GLM-5.2 (and even 5.1).
This has been my experience as well to the letter.
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#16GLM 5.2 edges as the safer pick when tasks are more challenging from-scratch builds and the result needs to arrive as a complete, runnable project. MiniMax M3 is the value pick for a lot of worker traffic.
I'd love to see a comparison with both Deepseek v4 models as well
There are some out there I couldn’t find one quickly, but deep seek reasons way too much
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#17Any comparison that brings "frontier-like" claims should have benchmarks against Opus 4.8 (or Fable 5 once we get it back) and GPT 5.5.
Spoiler alert: this article just says that GLM 5.2 is better in quality than MiniMax M3, but worse value for money.
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#18Earlier quoted context omitted.
I've been testing M3 for agentic tasks on Hermes and it just gets way too confused. I have really poor result from it compared to GPT-5.4 mini/regular or GLM-5.2 (and even 5.1).
This has been my experience as well to the letter.
M3 works best as a 'worker' agent. Create plans with a smarter model (Opus, K2.7, DeepSeek Pro) then use Minimax to execute.
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#195.2 is noticeably more security aware than 5.1
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
Re: MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
#20The comparison results seem very plausible. 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…
> For the coordinator or judge above them I would put myself 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 f…
Yeah, the comment you're responding doesn't understand the workflow being discussed. And of course that makes the person believe they're genius level on the topic