GLM cannot use vision like Opus can. This is not a useful comparison.
GLM 5.2 vs. Opus
91–100 of 367 posts
Re: GLM 5.2 vs. Opus
#92> GLM-5.2 cost a fraction as much. Opus finished in half the time and shipped a cleaner game. Off topic, but does anyone else instantly pick up on LLMisms like this? It seems like all the models have converged on this style of writing, and improvements aren't really changing it.
This is excellent feedback thank you! These LLMisms in writing are a challenge I am living with currently and trying to improve on. The technical writing industry is taking a huge knock right now with companies demanding more work in less time with a big drop in quality, day to day I get less and less time to work on the quality in the prose of my work. We are working at the frontier of this right now, so we are the most heavily effected, but also get to experiment with the changes first which can be both stimulating and very frustrating.
Re: GLM 5.2 vs. Opus
#93GLM cannot use vision like Opus can. This is not a useful comparison.
I see your point. Just the fact that one model does have vision and one does not might be an interesting point of comparison, however.
Re: GLM 5.2 vs. Opus
#94Earlier quoted context omitted.
It's true that no one is trying to one shot anything serious right now, but it's still an important metric. Claude Code and Opus really took off when they improved the harnessing enough that it would self-correct many of its mistakes without needing user input. In fact I think long-term autonomy (in the range of several hours) and self-correcting is going to be where we see most improvements in coming years.
it wont happen, its all a money grab.
I think that LLMs will stay, but I also think we've plateaued and that big companies will fail and fall and we will have another years long "halt" of any real advancements coming to the public.
Similar to how ML was all the hype about 12 years ago and then it submerged again for a couple of years.
Re: GLM 5.2 vs. Opus
#95I seriously dont' know all this big hullabaloo about one shot prompting. by definition, a single prompt wont' constitute the complexity of a software project. ergo, what you'll get is a series of assumptions made by the model based on preexisting code in its training corpus. I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventio…
I think you're underestimating the elegance of "hey build X". It already captures a lot of what you're interested in.
Additionally, with "Hey build X" nobody is happy with the methodology and people rightfully complain about the set up.
Using your suggestion the methodology would require a lot of presumptions & arguments regarding why you choose it and think it relevant to people.
Either people would not "get" it quickly enough or would disagree/not be interested on the setup because its not how they use LLMs.
Re: GLM 5.2 vs. Opus
#96I've signed up with Ollama to experiment with these open source models. For the past 3 months, it's just been experimenting, trying it out. GLM is the first model that I am using on a daily basis to do my coding work (as well as using Claude). It's good - I've been maxing out my Ollama usage limits everyday :)
Cool to hear, what kind of tasks have you been using GLM for? And what other models have you found useful through Ollama?
Re: GLM 5.2 vs. Opus
#97Re: GLM 5.2 vs. Opus
#98So GLM emits fewer tokens and does fewer tool calls, but still takes over twice as long to complete. Can someone explain to me where that time usage is coming from if not from the model operation itself? Are the individual tool calls more complex and take more time to complete? Or is the rate of tok/s lower because the model does more compute per token?
Could just be infra. I'm betting Anthropic is much better prepared.
Re: GLM 5.2 vs. Opus
#99I seriously dont' know all this big hullabaloo about one shot prompting. by definition, a single prompt wont' constitute the complexity of a software project. ergo, what you'll get is a series of assumptions made by the model based on preexisting code in its training corpus. I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventio…
That's precisely the difference between an engineer and a business guy.
The business guy would say "hey build me this and that" and would get _something_ to show of.
An engineer will have a long conversation with a llm about the exact requirements, tech stack, tradeoffs. He would understand what is built, how is it built, and refine on the fly until he gets something sensible.
It won't be as fast as "build this", but the result will be much better and more maintainable.
For the enginering workflow, you don't need Fable. Any model better or equivqlent to Sonnet 4.6 would do. Yes, sometimes it will hallucinate, sometimes it'll be wrong, but it's our job as engineers to correct it and have full ownership of the result.
Re: GLM 5.2 vs. Opus
#100Pretty clearly it's beating Opus at [web dev]( https://www.gptbased.com/ ) - on price, on score.. I mean what else is there?
Article states it's not multimodal. I guess that means for webdev it means you can't take a screenshot to indicate errors etc.