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Same task. Same prompt. Same setup.
Opus 4.8 completed the task.
It used 2% of the weekly limit and 7% of the 7-hour limit.
GLM 5.2 did not complete the task.
It consumed 20% of the weekly limit and 100% of the 5-hour limit.
Token usage is completely abnormal:
Opus 4.8: less than 1.5M tokens
GLM 5.2: reached 53M tokens
And this is despite the app showing only around 1.67M tokens.
This means one thing very clearly: cached tokens are not working properly on GLM 5.2. The repeated context is being counted as normal input instead of cached tokens.
I have been dealing with this issue for more than a month with no real solution.
By the way, I am on the Pro plan, and I paid for a full yearly subscription.
These numbers are not normal. This is not usage behavior. This is a serious billing/cache accounting problem on GLM 5.2.
@Iam_best_dev@BitGameHD@mersomas Nein. Der Satz ist zu Ende weil es impliziert dass man fragen kann
Wo ist mein iPhone?
Wo ist mein iPad?
Wo ist mein Mac?
Usw usf
Heißt nicht dass ich es selbst gut finde, Ich würde lieber kommandieren als fragen aber das ist wie Lokalisation funktioniert
@Iam_best_dev@BitGameHD@mersomas It's called localisation, an entirely different field from translation, that is used to make texts match different markets.
Apple determined, that Germans rather ask "where is my iPhone?" Than to tell it to "find my iPhone"
@reach_vb Graz, Austria. Been offering you guys to host it numerous times but never got a reaction, so I am now into month 3 of my general Agentic Coding meetup here
Honestly I'd say go ahead, but I think that's too much of a stretch in real life engineering. Let's be real about how for example Kimi k2.6 is more Claude Sonnet 4.5 level than anything else.
With that, if GLM 5.2 produces real life code of equal quality to GPT 5.2 or Opus 4.5 I'd already be incredibly happy