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by djx22 28 days ago
in my experience running models that have been heavily quantized(q4) or altered to some extent has never made me say “wow, this is so amazing”. On the contrary, the model ended up in the thrash bin after a few prompts. I have an RTX 6000 PRO with 96GB, and what I can run comfortably is Qwen 3.6 27B or MoE, Gemma 4 31B. This is as far as it goes when you run the model at full precision and maximum context length. They perform well and you can use them for coding, doing research on the internet and what have you. So if you do the math and you see yourself spending more than the $2400/year to Anthropic, then it might make sense to get one of these cards but accept the quality drop. Otherwise, will humans even be coding in 5 years from now?
1 comments

what you maybe forget here is the use case for people and businesses who can not send the data to 3rd party due to privacy/contractual reasons. This is what I'm looking at, we're bound by strict policies for data sharing outside of our premises.
yes, I understand the usecase. Where I'm coming from is quantized vs. unquantized. 4bit quants are lobotomizing the model heavily to the point that it's better to invest in some capable hardware than keep fighting the limitation. Refurbished server grade hardware is accessible. For the price of an RTX 6000 PRO you could probably get much more VRAM but 1-2 generations older.