Is Turboquant really a game changer?

r/LocalLLaMA
Generative AI Open Source AI

I am currently utilizing qwen3.5 and Gemma 4 model. Realized Gemma 4 requires 2x ram for same context length. As far as I understand, what turbo quant gives is quantizing k cache into about 4 bit and minimize the loses But Q8 still not lose the context that much so isn't k cache ram for qwen 3.5 q8 and Gemma 4 truboquant is the same? Is turboquant also applicable in qwen's cache architecture? because as far as I know they didn't tested it in qwen3.5 style k cache in their paper. Just curious, I started to learn local LLM recently submitted by /u/Interesting-Print366 [link] [comments.