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GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

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Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#161
post #5

It's looking like we'll have Chinese OSS to thank for being able to host our own intelligence, free from the whims of proprietary megacorps. I know it doesn't make financial sense to self-host given how cheap OSS inference APIs are now, but it's comforting not being beholden to anyone or requiring a persistent internet connection for on-premise intelligence. Didn't expect to go back to macOS but they're basically the…

you have 128GB strix halo machines for US$ ~3k

these run some pretty decent models locally, currently I'd recommend GPT-OSS 120GB, Qwen Coder Next 80B (either Q8 or Q6 quants, depending on speed/quality trade-offs) and the very best model you can run right now which is Step 3.5 Flash (ubergarm GGUF quant) with 256K context although this does push it to the limit - GLMs and nemotrons also worth trying depending on your priorities

there's clearly a big quantum leap in the SotA models using more than 512GB VRAM, but i expect that in a year or two, the current SotA is achievable with consumer level hardware, if nothing else hardware should catch up with running Kimi 2.5 for cheaper than 2x 512GB mac studio ultras - perhaps medusa halo next year supports 512GB and DDR5 comes down again, and that would put a local whatever the best open model of that size is next year within reach of under-US$5K hardware

the odd thing is that there isn't much in this whole range between 128GB and 512GB VRAM requirement to justify the huge premium you pay for Macs in that range - but this can change at any point as every other day there are announcements

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#163

I'd say that they're super confident about the GLM-5 release, since they're directly comparing it with Opus 4.5 and don't mention Sonnet 4.5 at all. I am still waiting if they'd launch GLM-5 Air series,which would run on consumer hardware.

I place GLM 4.7 behind Sonnet.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#164
post #161
post #5

It's looking like we'll have Chinese OSS to thank for being able to host our own intelligence, free from the whims of proprietary megacorps. I know it doesn't make financial sense to self-host given how cheap OSS inference APIs are now, but it's comforting not being beholden to anyone or requiring a persistent internet connection for on-premise intelligence. Didn't expect to go back to macOS but they're basically the…

you have 128GB strix halo machines for US$ ~3k these run some pretty decent models locally, currently I'd recommend GPT-OSS 120GB, Qwen Coder Next 80B (either Q8 or Q6 quants, depending on speed/quality trade-offs) and the very best model you can run right now which is Step 3.5 Flash (ubergarm GGUF quant) with 256K context although this does push it to the limit - GLMs and nemotrons also worth trying depending on you…

And you can get Strix Halo in a Laptop that looks and feels like a Macbook Pro that can run Linux if you buy an HP ZBook G1A.

Super happy with that thing, only real downside is battery life.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#169
post #91

Earlier quoted context omitted.

> doesn't make financial sense to self-host I guess that's debatable. I regularly run out of quota on my claude max subscription. When that happens, I can sort of kind of get by with my modest setup (2x RTX3090) and quantized Qwen3. And this does not even account for privacy and availability. I'm in Canada, and as the US is slowly consumed by its spiral of self-destruction, I fully expect at some point a digital iron…

Your $5,000 PC with 2 GPUs could have bought you 2 years of Claude Max, a model much more powerful and with longer context. In 2 years you could make that investment back in pay raise.

> In 2 years you could make that investment back in pay raise.

you can't be a happy uber driver making more money in the next 24 months by having a fancy car fitted with the best FSD in town when all cars in your town have the same FSD.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#170

Earlier quoted context omitted.

And you are forgetting the fact that things like vast.ai subscriptions would STILL be more expensive than Openrouter's api pricing and even more so in the case of AI subscriptions which actively LOSE money for the company. So I would still point out the GP (Original comment) where yes, it might not make financial sense to run these AI Models [They make sense when you want privacy etc, which are all fair concerns but…

Why did you quote yourself at the end of this comment?

Oops sorry. Fixed it now but I am trying a HN progressive extension and what it does is if I have any text selected it can actually quote it and I think this is what might've happened or such a bug I am not sure.

It's fixed now :)

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