I was quite surprised that Zai had deep pockets to serve this free for a week. My first guess was this was an American lab like xai or google
GLM-5.3-Flash
181–190 of 605 posts
Re: GLM-5.3-Flash
#182It looks like gemini 3.7 flash actually beats it in a lot of benchmarks, no?
Re: GLM-5.3-Flash
#183Chinese labs are so used to manipulating benchmarks to try to flatter inferior models that when they finally have one that's really pretty good I think the official announcement here undersells it. https://deepswe.datacurve.ai/ That's pretty solid. Smarter and cheaper than Luna xhigh, not as smart but less expensive than Luna max. Smashes deepseek v4 flash, and even worse it matches v4 pro at a tiny fraction the cost…
It's also better than Sol (at whatever effort) at designing pretty UIs. I have a Codex sub and I've been using this model for UI stuff.
> I've been using this model for UI stuff.
The flash one?
Re: GLM-5.3-Flash
#184Earlier quoted context omitted.
Maybe others have found otherwise, but I find the benchmarks drastically different to real world "feel" of a model, even within the same harness. I'm not sure if this just reflects personal interaction styles, or if it is indicative of benchmaxxing or unrealistic automated benchmarking methodology. Opus 5 consistently comes at or near the top, but outputs constant unreadable jibberish. Meanwhile GPT 5.6 Luna medium t…
I've been using 5.3 since they initially announced it and my gut feel is that it's not as good as 5.2 for agentic tasks. I'm still using it - I don't think it's bad. I'm just not convinced it's better.
idk i think that i spend significant tokens with both to be able to tell 5.3 is way better overall.
https://kommodo.ai/i/IFSUUQYT522uZXWvePZ1
it still fells stupid sometimes and it is benchmaxxed for sure. but its good enough that im building all the hobby projects with it.
Re: GLM-5.3-Flash
#185Chinese labs are so used to manipulating benchmarks to try to flatter inferior models that when they finally have one that's really pretty good I think the official announcement here undersells it. https://deepswe.datacurve.ai/ That's pretty solid. Smarter and cheaper than Luna xhigh, not as smart but less expensive than Luna max. Smashes deepseek v4 flash, and even worse it matches v4 pro at a tiny fraction the cost…
I don't know how anyone can actually use Luna max on ANY real workload. I've had Sol orchestrate a bunch of Luna agents, these agents were explicitly given small chunks of larger objectives and they still filled their entire context windows with just reasoning tokens, until compaction hit, and then reasoning again.
I've probably wasted a good 40% of my weekly usage on Luna Max agents just thinking and not writing a single line of code.
Re: GLM-5.3-Flash
#186This is going so fast! What a time to be on hackernews: July 16th: The "Kimi K3 moment" - China has caught up to Opus! 4 weeks later: GLM 5.3 - Same performance, but cut the amount of parameters and cost to a third! 12 days later: GLM 5.3 Flash - Almost GLM5.3 performance but cut the parameters in half, cut prices to a fifth and serving on Chinese chips!
except besides benchmarks, most of these models don't meet reliability of Sol/Opus in coding work. Opus unfortunately talks very weirdly so not a great out of the box experience
Re: GLM-5.3-Flash
#187Earlier quoted context omitted.
I get all that. Then alternatives are: - Grok - where I absolutely have 0 trust in X.ai's interst in "pushing humanity forward". - OpenAI and Anthropic - which seem to try to be building the biggest moat they can by pushing to ban open models. And at the same time want to be an Arbiter of what level of intelligence I can use. - Google and Meta - I don't need to talk about the practices of these companies. Yes, the te…
All the American companies you mentioned still follow American law and regulation. Skirting that blatantly has big consequences. Chinese companies do not follow American laws and there are absolutely no consequences for violating it. Moreover, the average American is not even aware of exactly what the legal/judicial environment is like in China. If your code and data is stolen, you can't fly to China and demand justi…
Aren’t those American companies sued because they didn’t follow American law?
Re: GLM-5.3-Flash
#188Ironically, our administration pushing for ban of the AI chips to China is forcing them to make smaller and more efficient models which seems like a requirement for running on Chinese chips. I wouldn’t be surprised this model was tailored to run purely on Chinese chips. Same thing with Deepseek MLA, the drastically lower KV cache memory requirement was born out of necessity so it runs on the Huawei chips.
Re: GLM-5.3-Flash
#189Earlier quoted context omitted.
Compare to the cost of professional-grade tools in other trades and craft hobbies. Sure, $4000 can be a lot of if you're a casual hobbyist or are struggle to meet everyday lifestyle costs, but it's definitely not "insane" if this is the trade you make your living from or if you've established a lifestyle that affords disposable income for your hobbies. And for some people, $4000 for a device you have complete control…
I am pretty confident that given a $200 subscription on any of the big labs, you're getting $4000-$8000 per month in subsidized tokens... do what you wan't with your dough... and I too have a spark that I got really early (October 2025), but no, economically it does not compare to what's runnable locally in terms of quality from the frontier models. Economically, it looks like for as long as there are subscriber plan…
Anecdotally, ~$500-1500/month token spend at API OpenAI/Anthropic pricing seems pretty realistic for full-time engineers at companies with "liberal but not unlimited" LLM spend policies.
This is of course anecdata. I know plenty of outliers, too. I know a principal engineer who uses many multiples of the number I quoted above. I am sure we also know many people making do with much much smaller budgets as well, via all kinds of well-discussed methods.
But, "$500-$1500 per month per full-time developer" is just kind of the personal mental baseline I use when making my decisions with regards to thinking about whether any of this makes any economic sense.
Re: GLM-5.3-Flash
#190Weights on HF here: https://huggingface.co/zai-org/GLM-5.3-Flash I decided to take the plunge and get myself four sparks at a decent price (and bought the QSFP cables from AliExpress because they are literally 1/2 the price of Amazon), even knowing Apple was going to release new hardware and there's probably a spark 2 on the horizon. It looks like this is going to be a decent fit for what I need. I've been experiment…
Qwen 3.8 27B is around Opus 4.8 level of capability on the Agentic Intelligence Index (52 vs 57). In my testing the locally hosted Qwen is good enough that looking at a given piece of work output I couldn't tell you which model was behind it. https://artificialanalysis.ai/models/qwen3-8-27b?models=gpt-...
As a counter to that - I've tried various flavors/quants/full weights and Qwen 3.8 27B has been entirely useless at anything non-trivial. Sure - it can do some boilerplate work (though, even armed with a well written spec and working within a very well known framework it went off the rails and did things in a way that were... um... questionable at best) but I don't see it as anything more than a personal assistant style model. Zero chance I'd "work" with it, I spent days trying to get it to do something for me that was usable that I didn't have to have reviewed and refined by a frontier level model or myself. Couldn't do it. The idea that qwen 3.8 27b is _anywhere near_ Opus 4.8 is laughable. Pure benchmaxxing.
DS4 Flash 0731, on the other hand, wildly opposite experience. Would recommend.
GLM 5.2 - even quanted down to a hybrid 4/3 bit setup is amazing for everything but the hardest/most complex stuff in the same projects/realm.