In case you're wondering what it takes to run it, the answer is 8x H200 141GB [1] which costs $250k [2].
1. https://github.com/MiniMax-AI/MiniMax-M1/issues/2#issuecomme...
1. this is apparently MiniMax's "launch week" - they did M1 on Monday and Hailuo 2 on Tuesday (https://news.smol.ai/issues/25-06-16-chinese-models). remains to be seen if they can keep up the pace of model releases for the rest of this week - these 2 were big ones, they aren't yet known for much else beyond llm and video models. just watch https://x.com/MiniMax__AI for announcements.
2. minimax m1's tech report is worthwhile: https://github.com/MiniMax-AI/MiniMax-M1/blob/main/MiniMax_M... while they may not be the SOTA open weights model, they do make some very big/notable claims on lightning attention and their GRPO variant (CISPO).
(im unaffiliated, just sharing what ive learned so far since no comments have been made here yet
"We publicly release MiniMax-M1 at this https url" in the arxiv paper, and it isn't a link to an empty repo!
I like these people already.
This is stated nowhere on the official pages, but it's a Chinese company.
Please come up with better names for these models. This sounds like the processor in my Mac Studio.
A few thoughts:
* A Singapore based company, according to LinkedIn. There doesn't seem to be much of a barrier to entry to building a very good LLM.
* Open weight models + the development of Strix Halo / Ryzen AI Max makes me optimistic that running great LLMs locally will be relatively cheap in a few years.
They apparently building buzz for an IPO
https://www.bloomberg.com/news/articles/2025-06-18/alibaba-b...
if they trained this scale without western cloud infra, i'd want to know what their token throughput setup looks like
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