> So we ran it head-to-head against Claude Opus 4.8: same one-shot prompt, build a 3D platformer in raw WebGL from scratch Running a single one-shot prompt is not a benchmark, not is it representative of any sort of real-world usage. Most agent usage is collaborative so you need to test things like reliability (when I delegate a task, does it complete it without making up test results for e.g.) and steerability (does…
Hi, I am the author, I completely agree! I set out to run a vibe test on this one, not a benchmark, the real benchmarks are listed. My test shows what the models can do when both tasked with a long-running, technically difficult, one-shot task. I think your test you describe (collaborative, task delegation, task completion, TTD, steerability) is a great format for a future test that I will definitely try out.
GLM 5.2 vs. Opus
281–290 of 367 posts
Re: GLM 5.2 vs. Opus
#282I 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.
Hi, author here, I cannot give an exact number for how many token the verification step took, but the verification GLM 5.2 ran was very stupid and definitely a waste of time. It read the pixel color data to try and verify the scene rendered properly. Which is really bad. Opus opened the game in a Playwright browser and took screenshots to verify the actual image. Which helped a lot. Pro tip: You could use a multi-mod…
Re: GLM 5.2 vs. Opus
#283I 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…
Re: GLM 5.2 vs. Opus
#284I 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…
In fact, I'd rather see Anthropic publish a convincing project that does this using Claude. The project should be complex enough and novel enough to show the world how reliable and powerful Claude is. That is, Anthropic does not need Amodei or its employees to tell us that whatever percent of engineers will lose their jobs. They can just show us. Easily.
Re: GLM 5.2 vs. Opus
#285Earlier quoted context omitted.
My pi usage over the past ~5 months went roughly like this: * Install pi and a bunch of extensions from their package repo * Realize that all the packages (with a few exceptions) are massively overcomplicated and vibe coded * Ask pi to rebuild a very simple version of the packages I used. So e.g. subagents - all the default subagent extensions are massively complicated with named agents, recursion, communication. I m…
What type of task are you running for ten hours? Is this a programming task? I've not come across a programming task that would take an LLM ten hours.
Re: GLM 5.2 vs. Opus
#286I feel like another comparison worth looking at is purely cost. Capability per dollar is something I care about: Opus API $5/$25 Sonnet API $5/$15 Haiku API $1/$5 GLM 5.2 API $1.4/$4.4 So you're really getting near opus level capability for the price of haiku .
Re: GLM 5.2 vs. Opus
#287One nice thing about GLM is that it has never refused a task. I'm working on a website that renders countries right now, and Anthropic's models regularly give me the old "This request triggered safety guardrails." I'm not sure what exactly triggers it, but it seems to happen when it has to look at lists of countries. I suspect there must be at least one country name that triggers the safety guardrail. You'd expect GL…
Part of me wants to believe they really do care about protecting the world from... something... I don't know quite what exactly tbh... but it must be costing them a small fortune to scan each input and output against N guardrails and they are a for-profit corporation who could easily turn a blind eye to all of this and simply say "what you do with this model is on you" like I would expect most corporations to.
Strange times.
Re: GLM 5.2 vs. Opus
#288It would be more interesting and accurate to see the comparison on the same harness if the intent is to compare the frontier models.
Pi is relatively new and does not have many features built-in compared to Claude Code. It was chosen intentionally this way as Pi's goal is not to create a bloat builtin of tools most don't use but to allow the users to customize to fit their need -- similar to Neovim vs IDE.
The end-user "vibe coding" experience is *heavily* swayed by the harness because prompt effectively drives how a model outputs an answer.
Re: GLM 5.2 vs. Opus
#289> 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.
There was this dude here not long ago who bought like $70k worth of gpus to research, and if I'm not mistaken his research was something related to make llms sound less llm-y. I wonder how it goes for him.
Re: GLM 5.2 vs. Opus
#290I feel like another comparison worth looking at is purely cost. Capability per dollar is something I care about: Opus API $5/$25 Sonnet API $5/$15 Haiku API $1/$5 GLM 5.2 API $1.4/$4.4 So you're really getting near opus level capability for the price of haiku .
Not really, GLM uses more tokens to get work done.