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GLM-5.3-Flash

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Re: GLM-5.3-Flash

#161

Post by drob518 »

seaal wrote: post #104
drob518 wrote: post #80

Earlier quoted context omitted.

Seems disingenuous to draw frontier graphs with starter pricing.

Well, Luna debuted with 5x higher pricing than is currently available. With the pace of recent development these models might not be relevant by Thanksgiving.

Of course. Pricing is always changing, but typically it goes down over time, not up. So, if you're showing artificially low pricing from the start based on a teaser rate, IMO, you shouldn't be using that to show where you appear on a frontier graph. Place yourself on the graph based on your expected long-term pricing. Then, over time, adjust your position based on your standard rate, whatever that might be. Games are always being played for things like this, but this seems excessive.

Re: GLM-5.3-Flash

#163

Post by KptMarchewa »

pietz wrote: post #141

With tiny models surpassing huge, 6 months old models on benchmarks, does anybody have some smart words to share on how these still "feel" different? Artificial Analysis ranks GPT 5.6 Luna similar to GPT 5.4, but that never matches my real world experience. AA seems to do a good job making a single number as representative as possible but there is still so much benchmarks don't communicate.

I agree. They are definitely good - no issues with instruction following for example - but they miss the "intelligence" larger models have.

For implementation tasks, where I have the problem already defined and researched, or just simple task, I'd definitely use something like Luna xhigh or max. If the task is vague, or involves planning, I'd rather use Sol medium, even though it's theoretically worse on benchmarks.

Re: GLM-5.3-Flash

#164

Post by overgard »

chews wrote: post #96
swatcoder wrote: post #69

Earlier 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…

The cloud stuff is definitely a much better economic value, but I would argue:

1. You learn a lot more running this stuff yourself (especially since you can poke at its internals if you're interested or watch the reasoning chain.) Just being a consumer of this stuff doesn't really teach you much about it other than model & harness specific tricks that become obsolete pretty quickly. (IE, your Claude.md from 6 months ago probably needs a rewrite). Which is fine, I don't think you're going to be "left behind" if you're not a hardcore AI enthusiast or anything (I'm not), but as a guy that's always been interested in computer science I want to see how it ticks.

2. You can't really depend on this subsidization lasting forever IMO. I know the financials thing has been beaten to death but I guess I'm in the camp that it's good to be in control of your tools so that you can go elsewhere if the economics change.

I like to check in with ccusage pretty frequently, and honestly like if I were paying API prices for Claude I'd probably be paying thousands a month.

Re: GLM-5.3-Flash

#165

Post by BeetleB »

mrinterweb wrote: post #160
BeetleB wrote: post #153

The key difference between this and all other GLM models is it's multimodal. You cannot send images to the other GLM models.

I really wish GLM models had vision capabilities. I've worked around that in the past to use a vision MCP in my harness that GLM can call. It is not the same, but it allows the model to query images.

Well, now one of them does!

Re: GLM-5.3-Flash

#166

Post by jrockway »

chews wrote: post #96
swatcoder wrote: post #69

Earlier 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…

I am also not sure I would choose to use the cheap and easy to run at home model, given a choice. The marketing copy says this is a frontier model, but it's not. Sol and Mythos are the frontier right now. GLM 5.3 Flash simply isn't. I'd rather use the frontier model as they waste less of my time than even Opus.

Re: GLM-5.3-Flash

#167

Post by bertili »

This 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!

Re: GLM-5.3-Flash

#168

Post by metadat »

mmastrac wrote: post #7

Weights 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-...

Re: GLM-5.3-Flash

#169

Post by pshirshov »

epolanski wrote: post #4

I'm starting to think that this whole sanctioning China may motivate and prompt them to do more and better in every field. It's too big, bright and resourceful of a country to choose confrontation instead of collaboration.

> I'm starting to think

That's good. Keep going.

Re: GLM-5.3-Flash

#170

Post by lukan »

overgard wrote: post #164
chews wrote: post #96

Earlier quoted context omitted.

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…

The cloud stuff is definitely a much better economic value, but I would argue: 1. You learn a lot more running this stuff yourself (especially since you can poke at its internals if you're interested or watch the reasoning chain.) Just being a consumer of this stuff doesn't really teach you much about it other than model & harness specific tricks that become obsolete pretty quickly. (IE, your Claude.md from 6 months…

3.privacy

Any organisation or individuals not wanting to have their sensitive data flowing away (either because of trade secret or data protection laws)

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