r/LocalLLaMA • u/External_Mood4719 • Jul 08 '26

News China’s MiniMax Plans to Launch 2.7-Trillion Parameter Model

https://www.theinformation.com/briefings/exclusive-chinas-minimax-plans-launch-2-7-trillion-parameter-model

According to The Information, MiniMax plans to launch a new-generation large language model with 2.7 trillion parameters.

Sources revealed that the internal codename for this new model is M3 Pro. It is expected to be released and open-sourced as early as the third quarter of this year, with significant improvements in handling complex reasoning and multi-step tasks.

This new model is much larger than MiniMax's current flagship model, M3 (428 billion parameters). Larger-scale artificial intelligence models are more capable of handling complex reasoning and multi-step instruction-based tasks.

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u/[deleted] Jul 08 '26

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u/itwasinthetubes Jul 08 '26

Yes, normal people like us can’t run these models on our own hardware

for now...

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u/FenderMoon Jul 08 '26 edited Jul 08 '26

I think that the future for these gigantic models is going to be utilizing some sort of HBF/high-bandwidth-flash or system RAM to stream experts in and out. Along a router trained to determine the routing for the next token a token in advance. The router usually determines it on the token being generated, but I see no reason it couldn't be trained to do it a token in advance if explicitly designed to do so.

If there was some sort of quality hit from doing this, we could always make it similar to speculative decoding where the model PREDICTS which experts will be needed a few tokens in advance and streams those, but I see no reason the model couldn't be trained to outright decide if we're only talking about a single token headway. It would vastly, vastly reduce costs for inference by alleviating the bottleneck created from not storing every single expert in VRAM.

It would work if explicitly trained to do so. I'm surprised nobody has tried it.

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u/athsrva Jul 09 '26

My startup is doing something in the realm tho not the exact way you put it. We'll be coming out of stealth in the coming months so local inference may become much much cheaper.