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Memory prices tipped to fall as China starts flooding the market with DRAM and NAND chips
(www.techspot.com)
this post was submitted on 22 May 2026
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Same. I'm running Qwen3.6-35B-A3B-FP8 (Qwen3.6-35B-A3B-UD-IQ4_XS.gguf) via the turboquant fork of llama.cpp with a few tweaked memory settings, and I get like 40 tokens / second -- nothing that required special insight on my part just following the instructions I saw on a youtube video I found via !LocalLLaMA@sh.itjust.works and asking claude to help me through the installation.
AI has no economic moat. There's nothing stopping anyone from running LLMs locally.
I just updated my setup from LMStudio to llama.cpp with the new QWEN 3.6 27B MTP model and I am getting 80-112 tokens/second, 90 average which is just shocking to me. I am on a 4090 with a context Window of 64k. It hardly use cloud AI anymore as I rarely need more than 64k if I ensure my first prompt is written like a design document. Multiple prompts are not great so I often just figure out where my initial prompt went wrong, adjust and try again in a fresh session. Way faster this way too. It has really worked out well for me as I am getting just as much done locally for free as I was with hundreds of dollar a month on cloud AI. I am still shocked and grateful it flowed this way.
What do you run it on?