𝗦𝗽𝗹𝗶𝘁 𝗟𝗟𝗠 𝗧𝗮𝘀𝗸𝘀 𝗕𝗲𝘁𝘄𝗲𝗲𝗻 𝗚𝗣𝗨 𝗮𝗻𝗱 𝗖𝗣𝗨

𝗦𝗽𝗹𝗶𝘁 𝗟𝗟𝗠 𝗧𝗮𝘀𝗸𝘀 𝗕𝗲𝘁𝘄𝗲𝗲𝗻 𝗚𝗣𝗨 𝗮𝗻𝗱 𝗖𝗣𝗨

LLMs treat math like poetry. They use one model for language and for calculations. This leads to errors.

GPUs process symbols and numbers with the same logic. Your CPU and RAM often sit idle. This waste of resources hurts performance.

You need a hybrid system.

• GPU handles symbols and user intent.
• CPU handles formulas and precise math.
• A routing gate sends the task to the right side.

This system stops the model from guessing numbers. You get stable results. You lower your costs.

These ideas come from testing Grok and Gemini. A non-programmer found this through observation.

Source: https://dev.to/__d04775ef9dd1f/o-vviedienii-razdielieniia-zadach-miezhdu-gpu-i-cpu-vnutri-llm-1m6i Optional learning community: https://t.me/GyaanSetuAi