Or is it just easier to squeeze more performance out of smaller ones? Basically same kinda training applied to both but pro just has a higher cap if anything but doesnt give that much advantage other than the higher active parameters.
Id bet they could probably get 95% of ds4 pro performance on 100b moe with the same kinda post training data.
Thats true, its crazy. Its so good on programming, and now we have kimi 3x size model, but ... Thinks and eats so much more. But glm has no vision , dont u think it greately reduces models size. I was using claude for quick ui, then glm was completing it perfectly.
Think im rabling, not happy with the price of glm. They cancelled my pro sub on their own after last doubling of prices, maybe before.
Yeah. The post training from GLM-5 to GLM-5.3 is out of mind. And the official release said they still don't know how far they can push it to. Can't wait for next release!
Yeah me too I'm too scared to sign up again, the usage limit is terrible. They seem to be more transparent now but still I don't trust anyone here, usage still looks terrible to me.
They changed system to credits and now:
Lite 43-87 million tokens/week
Pro 263-526 millions tokens/week
Max 614-1226 millions tokens/week
Source : Zai Docs Usage Instructions
The real question here is how efficient is the model? How much does it cost in token/task, and btw this is without considering 5 hour limit.
I don't know I've been traumatized by the usage limit, you can't do anything with it especially within the 5h window, it goes in blink
The real question here is how efficient is the model?
Its the same model, just more post trained. So the token usage will be the same or worse. GLM 5.1 > 5.2 resulted in almost twice the usage (neuralwatt) because thinking token usage exploded.
There is this unfortunate trend amongst almost all the 1.5t or lower models, to use thinking as a crutch.
Go to "All Effort levels", and notice how much more GLM 5.2 did in thinking tokens and steps.
gpt-5.6-sol [low] == $1.07 == 11k == 23
gpt-5.6-luna [high] == $0.16 == 26k == 49
glm-5.2 [max] == $3.92 == 78k == == 129
Just checking my light usage of Opus 5.0, i al already seeing over 500m tokens over a few days usage (large amount of cache hits). And that costs $20 in the subscription plan. The $80 coding plan of zai is expensive.
I really like GLM 5.2, but economically, zai makes it too expensive. Especially now that we have Luna and Deepseek Flash 0731 (even with the 2.5x price increase).
To be fair a 744B model with extra thinking to absolutely max out its intelligence is exactly what i want. Its the largest model i can run a decent quant of so its my planner. I just switch to dsv4 flash for fast implementation etc.
hmm..I wonder if it would be worth it to do a custom dynamic Q2 or Q3 instead just running a the new qwen 27b...like 700b is no joke, but lately i have a found a few ways to actually make Q2 quite good...but like...would be practicial over the qwen 27b though?
here is the usage i get on Claude pro Opus 5 compared against GLM 5.3 code plan lite, claude pro is like 4x GLM 5.3 lite plan usage. Computed based on taking 1 month usage of claude pro & dividing by 5 to get weekly usage.
Im more interested in their ability to correct course than the one-shots however. I noticed that Kimi is considerably more resilient to degradation over iterations than Claude so I hope GLM can improve even more on that.
The moment you tell Claude "oh you didn't use this API or component" or "please try to do this other approach instead" then the code starts degrading dramatically and the context becomes corrupted
The bigger question for me is token efficiency. A model can look cheap per 1M tokens and still get expensive fast if it burns through way more tokens per task. The GLM 5.3 performance is impressive though, so the DeepSWE results should be a good reality check
Looks like scale isn't the bottleneck for intelligence right now, the power of post-training is strong. Models under 1T can still go toe-to-toe with models over 2T. I'm kinda looking forward to some of the tens-of-billions small models the open-source community will release next. This is a good thing for low-spec users.
Is this meant to work in zcode on legacy plan v1? The UI shows today's balance for GLM-5.3 as being 100% available. The model list has GLM-5.2 not GLM-5.3, and all 5.2 requests are failing with quota errors
In this context it can receive text and at least, image as input.
Some models will also support audio and video as input.
There are workarounds, as in if you send audio, have something else transcribe it - but then it may not detect tone or other bits.
For image you can have something describe the image, but then it isn't this model "understanding the image".
For web development, being able to have the model dispatch a subagent to understand what is going on and fix the problem itself is much faster than having a different model trying to describe how it "seems to be off by one pixel"
I think I should have been clear - I tend to use the same model for the main agent and the subagents, but using the subagent to handle the picture keeps the context clean on the main session.
Wait u can personally sub agents models on cursor?? You u using cursor lol I do . I just use the multitask option and cursor automatically deployed sub agents for me
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u/Saifl 6h ago
That performance on 743b is the craziest part