

I’ve been running the Ridge-GGUF version on my RX 9070 XT with ~60-80k contextsize with q4 kv cache quantization. Everything fits completely in 16GB VRAM


I’ve been running the Ridge-GGUF version on my RX 9070 XT with ~60-80k contextsize with q4 kv cache quantization. Everything fits completely in 16GB VRAM


no it is not fundamentally unethical. Please stop perpetuating this stupid take. AI is not designed to do unethical things. The profit motive drives companies to doing unethical things with it. If it weren’t for AI, they’d use something else.
Please don’t lose sight of the root cause of the problems, which is profit above everything. Equally you could say that fossil fuel combustion engines are fundamentally unethical because they cause climate change and all sorts of health issues.
Most technologies are neither ethical nor unethical. It is how you use them and what for that might be ethical or unethical. Sure they can be more or less useful. We can argue about that. But technology itself is orthogonal to ethics. Unless it is nukes or anything that is explicitly designed to do harm and nothing else.


slightly off topic:
as a german and a software dev, i have to say QWERTZ sucks. Everyone should just adopt the english international layout.
I have nothing really to compare it to in terms of the big ones because i refuse to give anthropic/openai any money. But i have used this qwen model in opencode to port an old CUDA/Optix based project to HIP and that worked fairly well. Not an overly complex refactor to be honest because 99% is just replacing the cuda prefix everywhere with hip, but it did fix the CMakeLists.txt for me and ported the optix prime acceleration structure to hipRT as well. I also let it vibecode a react based portfolio page because i have absolutely 0 knowledge of web development and refuse to learn it because i think it is insane and that turned out perfectly fine as well.
So it is absolutely usable for real world projects and the performance is quite OK as well with ~35tok/s. If i up the context size to the full 256k window, the performance drops to 5 tok/s, which is ok, if i let it do a boring refactor over night but at that point it isn’t faster than running DeepSeekV4.1-Flash-1017 through Strata and that one is much closer to the current SotA.
Definitely exciting times. We are close to being able to run very capable LLMs locally that are more than good enough for development. I am personally not a fan of 100% vibe coded projects anyway, because i like to architect things myself, so letting it go in smaller steps and/or help be with the boring stuff is absolutely fine. Unless the project is some personal stuff that just needs to solve one simple problem then vibe coding is fine imho.