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by xlii12 hours ago |
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upvoteby nijave4 hours ago|
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>it takes it sweet time to get code rolling, not the fastest model by any means

Which provider are you using? I got a z.ai Lite Coding Plan and it's my understanding z.ai is on the slower side of providers and the Lite plan gets lower priority on top of that. In the api key console, it shows dipping below 60 tok/sec which is quite slow.

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upvoteby trollbridge8 hours ago|
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I used it the other day for something of low importance that other models simply weren't figuring out and I didn't want to burn up Opus 4.8 on. (It had to do with overriding left-click on a macOS menu bar and then making Ctrl+click or right click bring up the menu like left-click normally does, and doing all this conditionally.)

Switched the model to GLM-5.2 halfway in the middle of a troubleshooting session (didn't even bother to reprompt, just changed it in the middle of its reasoning), gave it a few minutes, problem fixed. This is with the subscription based allocation on OpenCode Go, where a problem like this would completely burn up my Opus for the current 5 hours or even the current week.

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upvoteby jeremyjh9 hours ago|
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Its also nice that you can see its entire reasoning trace. I can see it going off the rails - or see something I forgot to tell it - and stop and correct it. Or I'll learn WHY it made the choice it did and not have to question it after.
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upvoteby jauntywundrkind8 hours ago|
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Strong agree! I deeply appreciate this aspect of GLM. Watching it think & being able to nudge early is incredibly useful. Being able to point at bad assumptions is incredibly useful. Watching what it's seeing is super informative.

It's always a shock to me how opaque most other models are!

It also is pretty resilience to letting you inject in while it's working without going off course or while getting back on track after, which I appreciate

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upvoteby Sanzig6 hours ago|
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> It's always a shock to me how opaque most other models are!

This is (unfortunately) by design. The proprietary models hide their reasoning traces so they can't be used for model distillation. Sometimes even when they do show reasoning, it isn't the model's real trace - IIRC, someone was able to demonstrate that Opus' reasoning is usually a summary made with Haiku behind the scenes.

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upvoteby braebo4 hours ago|
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It is such a momentum killer being forced to stare at a silly word for 4 minutes instead of being able to read the thinking as it streams in. I can’t wait until I can drop Anthropic at work. Their UX sucks, intentionally, for anti competitive reasons like “don’t distill our model we trained on all the data & IP we stole and processed with the mass exploitation of data workers in the global south!”.
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upvoteby Oras11 hours ago|
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Also pricing, I wanted to give a try, but when pricing is only 30% cheaper than Opus, I wouldn't go for it with these issues.
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upvoteby nijave4 hours ago|
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z.ai coding plan is a fairly decent deal at ~$16/mon USD considering it's supposed to have a fair bit more usage than the comparable $20/mon Claude plan. On the other hand, z.ai seems a bit on the slower side for raw model tok/sec throughput.
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upvoteby chpatrick9 hours ago|
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It's pricing is a lot cheaper if you can run it yourself.
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upvoteby nijave4 hours ago|
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Not this one. It's a SOTA-class model >800Gi VRAM required at fp8
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upvoteby jeremyjh8 hours ago|
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What?

It is less than 20% of the cost of Opus at API rates. 1.40/4.40 vs 5/25.

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upvoteby cmrdporcupine7 hours ago|
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Not when you factory in token efficiency. It burns a lot more tokens to do the same job, so when I compared to GPT5.5 I was frankly not really much ahead, and with weaker thinking.

Maybe makes sense if you have z.AI's (not greatly priced) subscription plan, but it's not competitive against an OpenAI or Anthropic monthly coding subscription plan. I burned through almost $10 worth of tokens just doing an hour of work.

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upvoteby Sanzig5 hours ago|
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Take a look at Ollama Cloud: https://ollama.com/pricing

You get access to a whole bunch of bleeding edge open models including GLM-5.2, Kimi K2.7, DeepSeek 4 Pro, etc. Inference is run on US/SG/EU cloud providers with zero data retention policies. The $20/mo tier is very generous, in my experience.

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upvoteby jeremyjh2 hours ago|
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They don’t have a statement about where it is run or data retention on the GLM5.2 model. They do state that for others, like MiniMax.
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upvoteby Sanzig1 hours ago|
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There's a blanket statement at the bottom of the pricing page, which I would hope also applies to GLM-5.2:

> Where are models hosted?

> Ollama hosts models and compute resources primarily in the United States. To serve global demand, we may route to Europe and Singapore for additional capacity.

> Is my prompt or response data trained on?

> Prompt or response data is never logged or trained on.

> Who does Ollama partner with to host models?

> Ollama collaborates with NVIDIA Cloud Providers (NCPs) to host open models.

> When Ollama partners with providers, we require no logging, no training, and zero data retention policies in place.

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upvoteby Imanari11 hours ago|
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This mirrors my experience. I have been using it in Pi. It is smart and output is good but it is not efficient in getting there.
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upvoteby ju-st11 hours ago|
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which thinking level? max or high?
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