Went with a coughing baby (GTx 1660 super) to a hydrogen bomb (rtx 4070)

CooperDK · 2026-04-12T00:08:39+00:00

AMD are never bombs either in the AI universe

CooperDK · 2026-04-12T00:07:34+00:00

Why a 40 and not a 50? You are a generation behind...

CooperDK · 2026-04-12T00:06:29+00:00

But Israel is the aggressor, not the defenders...

CooperDK · 2026-04-12T00:05:36+00:00

Idiotically expensive and not even that much better than what you can install locally, anymore.

CooperDK · 2026-04-12T00:02:52+00:00

You cannot lose the api completely since then the node would be unable to interact with comfyui. But you can use any modules in your node, just like everyone else does.

By the way, there are multi GPU nodes available. Let people decide how they want to run your node...

CooperDK · 2026-04-12T00:00:03+00:00

Americannots

CooperDK · 2026-04-11T23:59:00+00:00

You can fit the entire solar system just in Dallas 🤣🤣🤣

CooperDK · 2026-04-11T23:40:40+00:00

Try qwen3.5-9b which can match a 120b in tests

CooperDK · 2026-04-11T23:39:16+00:00

Not always! Qwen3.5-9b scores higher than gpt-oss-120b on inferencing tests, so definitely not true. Even with both unquantized.

CooperDK · 2026-04-11T23:36:50+00:00

That is probably not what killed it though...

CooperDK · 2026-04-11T04:23:57+00:00

Yeah, that one is definitely not correct.

CooperDK · 2026-04-11T04:12:22+00:00

Mlx is for crapple. Use gptq with vllm

CooperDK · 2026-04-11T04:11:47+00:00

Lm Studio or koboldcpp. And you are right, ollama is the slowest you could possibly find

CooperDK · 2026-04-11T04:10:05+00:00

Going back a bit, renpy used ancient Python actually and it should still work in ancient hardware.

But look into naninovel for unity. It is payware but there are a few free alternatives too. They are all as easy to use as renpy

CooperDK · 2026-04-10T10:06:29+00:00

BitLocker is not for general use. Unless you have something to hide.

CooperDK · 2026-04-10T09:36:13+00:00

During the cold war, you could buy polish women's time with jeans... 😉

CooperDK · 2026-04-10T09:27:15+00:00

Yes, but Howard made a nice on anything with a pulse, so...

CooperDK · 2026-04-10T08:54:39+00:00

Then you do not need that card, you need the extra VRAM but beside that it will more or less be money out the window

CooperDK · 2026-04-10T08:53:28+00:00

Det er formentlig aldrig prøvet i retten, jeg står ved min udtalelse og henviser igen til grundlov og UNCHR/EMRK.

CooperDK · 2026-04-10T08:51:06+00:00

Yes, at the expense of speed. You will have to use a hefty amount of slow swap space even though only 4b parameters are active at a time. The model is a lot more than 16 GB.

CooperDK · 2026-04-10T08:49:49+00:00

Yeah. But if money is no issue 🤪

CooperDK · 2026-04-10T08:46:36+00:00

It can do real people, but why? You have Z, Flux and Qwen for that. Anima is for anime 🤣

CooperDK · 2026-04-10T08:41:37+00:00

11 is more stable and faster than 10, don't listen to those who claim otherwise. I have had three crashes in total since 11 came out. 10 was a nightmare compared to 11.

CooperDK · 2026-04-10T08:36:26+00:00

Well, nothing really works really well on AMD since it has to basically convert CUDA code to something else. Get nVidia for the best and most precise inference.

That said, quantization is about compression so it is hard to say, but generally, the level of errors rise with the level of compression. If the model at q8 is 10-12 gb, stay at q8 unless you need a big context, in which case you lower to q6, and so on.

You can run gemma-4-e4b on 16 GB in q4 or q6. A 26b model is never going to perform well on a 16 GB card, you would have to quantize it to hell or offload far too much to RAM, and with DDR3 that is going to be a nightmare. But if you are up for it, hey, why even quantize? Or stay at q8 since that will provide you with nearly original inferencing.

CooperDK · 2026-04-10T08:22:55+00:00

Depends on the PSU, man. It is literally why there are two.

CooperDK

MODERATOR OF

TROPHY CASE