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GLM-5.1: Towards Long-Horizon Tasks

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Re: GLM-5.1: Towards Long-Horizon Tasks

#181

Post by marcus_holmes »

kcb wrote: post #174
marcus_holmes wrote: post #172

Earlier quoted context omitted.

Sorry, I don't understand that comment. Can you clarify, please?

My point is LLMs aren't more usable if the hardware is in your room versus a few states away. Personal computers still to this day aren't great when the hardware is fully remote.

Agreed. But you couldn't do much on a PC when they launched, at least compared to a mainframe. The hardware was slow, the memory was limited, there was no networking at all, etc. If you wanted to do any actual serious computing, you couldn't do that on a PC. And yet they ate the world.

I can easily see the advantage, even now, of running the LLM locally. As others have said in this topic. I think it'll happen.

edit: thanks for clarifying :)

Re: GLM-5.1: Towards Long-Horizon Tasks

#182

Post by dvt »

bottlepalm wrote: post #168
dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

This has got to be bait.. 1) OpenAI and Anthropic are killing it, and continue to do so, their coding tools are unmatched for professionals. 2) Local models don't hold a candle to SOTA models and there's nothing on the horizon that indicates that consumers will be able to run anything close to what you can get in a data center. 3) Coding is a killer product, OpenAI and Anthropic are raking in the cash. The top 3 apps…

I don't want to respond to 100 comments about the same thing, and this one happens to be on top, so, in my humble opinion:

(1): You don't have to be an Ed Zitron disciple to infer that OpenAI and Anthropic are likely overvalued and that Nvidia is selling everyone shovels in a gold rush. AI is a game-changing technology, but a shitty chat interface does not a company make. OpenAI and Anthropic need to recoup astronomical costs used in training these models. Models that are now being distilled[1] and are quickly becoming commoditized. (And frankly, models that were trained by torrenting copyrighted data[2], anyway.) Many have been calling this out for years: the model cannot be your product. And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing.

(2): Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. The end-state here is likely some models running locally and some running in the cloud. But the current state of OpenClaw token-vomit on top of Claude is fiscally untenable (in fact, this is why Anthropic shut it down).

(3): This is typical Dropbox HN snark[3], of which I am also often guilty of. I really don't think AI coding is a killer product and this seems very myopic—engineers are an extreme minority. Imo, the closest we've seen to something revolutionary is OpenClaw, but it's janky, hard to set up, full of vulnerabilities, and you need to buy a separate computer. But there's certainly a spark there. (And that's personally the vertical I'm focusing on.)

[1] https://www.anthropic.com/news/detecting-and-preventing-dist...

[2] https://media.npr.org/assets/artslife/arts/2025/complaint.pd...

[3] https://news.ycombinator.com/item?id=9224

Re: GLM-5.1: Towards Long-Horizon Tasks

#183

Post by csomar »

alex7o wrote: post #20

To be honest I am a bit sad as, glm5.1 is producing mich better typescript than opus or codex imo, but no matter what it does sometimes go into shizo mode at some point over longer contexts. Not always tho I have had multiple session go over 200k and be fine.

I've set max context to 180k and usually compact around 120k. It's much better to re-read stuff than to have it under-perform when it's over 120k.

Re: GLM-5.1: Towards Long-Horizon Tasks

#184

Post by BoorishBears »

XCSme wrote: post #126
jaggs wrote: post #39

How does it compare to Kimi 2.5 or Qwen 3.6 Plus?

General intelligence (not coding) comparison: https://aibenchy.com/compare/z-ai-glm-5-medium/z-ai-glm-5-1-...

Is there really no rule that discourages 99% of your interactions with HN from being peddling some useless slop benchmark?

Re: GLM-5.1: Towards Long-Horizon Tasks

#185

Post by acchow »

kcb wrote: post #161
deminature wrote: post #131

Earlier quoted context omitted.

Intel has just released a high VRAM card which allows you to have 128GB of VRAM for $4k. The prices are dropping rapidly. The local models aren't adapted to work on this setup yet, so performance is disappointing. But highly capable local models are becoming increasingly realistic. https://www.youtube.com/watch?v=RcIWhm16ouQ

That's 4 32GB GPUs with 600GB/s bw each. This model is not running on that scale GPUs. I think something like 96GB RTX PRO 6000 Blackwells would be the minimum to run a model of this size with performance in the range of subscription models.

> I think something like 96GB RTX PRO 6000 Blackwells would be the minimum to run a model of this size with performance in the range of subscription models.

GLM 5.1 has 754B parameters tho. And you still need RAM for context too. You'll want much more than 96GB ram.

Re: GLM-5.1: Towards Long-Horizon Tasks

#186

Post by csomar »

RickHull wrote: post #14

I am on their "Coding Lite" plan, which I got a lot of use out of for a few months, but it has been seriously gimped now. Obvious quantization issues, going in circles, flipping from X to !X, injecting chinese characters. It is useless now for any serious coding work.

I have their most expensive plan and it's on-par and sometimes better than Claude although you have to keep context short. That being said, the quota is no longer generous. It's still priced below Claude but not by that much. (compared to a few months ago where your money gets you x10 in tokens)

Re: GLM-5.1: Towards Long-Horizon Tasks

#187

Post by csomar »

InsideOutSanta wrote: post #91
RickHull wrote: post #14

I am on their "Coding Lite" plan, which I got a lot of use out of for a few months, but it has been seriously gimped now. Obvious quantization issues, going in circles, flipping from X to !X, injecting chinese characters. It is useless now for any serious coding work.

My impression is that different users get vastly different service, possibly based on location. I live in Western Europe, and it works perfectly for me. Never had a single timeout or noticeable quality degradation. My brother lives in East Asia, and it's unusable for him. Some days, it just literally does not work, no API calls are successful. Other days, it's slow or seems dumber than it should be.

Their distribution operation is very bad right now. The model is pretty decent when it works but they have lots of issues serving the people. That being said, I have had the same problems with Gemini (even worse in the last two weeks) and Claude. So it seems to be the norm in the industry.

Re: GLM-5.1: Towards Long-Horizon Tasks

#188

Post by nareyko »

gertlabs wrote: post #179

We're still adding samples, but some early takeaways from benchmarking on https://gertlabs.com : Contrary to the model card, its one-shot performance is more impressive than its agentic abilities. On both metrics, GLM 5.1 is competitive with frontier models. But keeping in mind this is an open source model operating near the frontier, it's nothing short of incredible. I suspect 2 issues with the model are keeping it…

[dead]

Re: GLM-5.1: Towards Long-Horizon Tasks

#189

Post by doctorwho42 »

sunir wrote: post #164
zozbot234 wrote: post #152

Earlier quoted context omitted.

Coding assistants are currently quite hard to run locally with anything like SOTA abilities. Support in the most popular local inference frameworks is still extremely half-baked (e.g. no seamless offload for larger-than-RAM models; no support for tensor-parallel inference across multiple GPUs, or multiple interconnected machines) and until that improves reliably it's hard to propose spending money on uber-expensive h…

Computers get better and cheaper. That’s not a forever problem.

Source?

GPU and RAM prices have definitely not made consumer PC's cheaper than they were before bitcoin blew up or before AI blew up.

Maybe you could make an argument that they are more cost efficient for the price point... But that's not the same as cheaper when every application or program is poorly optimized. For example why would a browser take up more than a GB or two of RAM?

And I'd postulate that R&D to develop localized AI is another example, the big players seem hellbent that there needs to be a most and it's data centers... The absolute opposite of optimization

Re: GLM-5.1: Towards Long-Horizon Tasks

#190

Post by DeathArrow »

gertlabs wrote: post #179

We're still adding samples, but some early takeaways from benchmarking on https://gertlabs.com : Contrary to the model card, its one-shot performance is more impressive than its agentic abilities. On both metrics, GLM 5.1 is competitive with frontier models. But keeping in mind this is an open source model operating near the frontier, it's nothing short of incredible. I suspect 2 issues with the model are keeping it…

It would be nice if you can test the model with different harnesses, Z.ai's own Z Code, Claude Code, Open Code, Pi, Cursor etc.

My impression is that the choice of harness matters a lot.

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