Fahim In Tech
@fahimintech
1/ MiniMax-M1 just dropped and it’s beefy. we’re talkin' 456B params (with only ~46B active), a wild 1 million token context window, and a hybrid MoE architecture that keeps it lean & mean. it’s like the giga-brain cousin of DeepSeek-R1 on turbo mode 💥
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Fahim In Tech
@fahimintech
2/ the game changer here is “Lightning Attention” a new trick that slices the compute down to 25% for long docs. basically, it reads a book and doesn't melt your GPU. throw in smart reinforcement learning and boom, it can do math, code, AND multi-turn reasoning in one go 🧠
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Fahim In Tech
@fahimintech
3/ in benchmarks, M1-80k is crushing it. 86% on AIME math (that’s elite-tier), plus strong tool use, coding, and long context retention. it’s giving "serious Claude 3 vibes" but open source and ready to run on your own infra 🔓
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Fahim In Tech
@fahimintech
4/ and get this it also ships with an AI agent. it can search the web, execute code, build apps or decks, and work like a real assistant. it’s like if GPT-4 + Copilot had a hacker baby and it decided to go open-source for the culture 🧑💻✨
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Fahim In Tech
@fahimintech
5/ TLDR: MiniMax-M1 isn’t just a model drop, it’s a full open agent stack with top-tier reasoning, insane context length, and no vendor lock-in. if you’re a dev or researcher? this one’s your new playground 🎡
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Fahim In Tech
@fahimintech
Sources: https://github.com/MiniMax-AI/MiniMax-M1 https://venturebeat.com/ai/minimax-m1-is-a-new-open-source-model-with-1-million-token-context-and-new-hyper-efficient-reinforcement-learning/ https://www.analyticsvidhya.com/blog/2025/06/minimax-m1/
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