moe

🚨 $KIMI SHRINKS 2.78T PARAMETERS INTO 8GB RAM — WITHOUT A GPU! 💥

🔍 This open-source experiment challenges every assumption about inference scaling. A 176KB pure C99 project runs Kimi K3's 1.56TB weight set on just 8GB of memory by streaming expert weights from NVMe storage on demand. 💡

The magic is MoE sparse activation — only 16 of 896 experts are active per layer. So the developer trades flash storage bandwidth for RAM, treating disk like a slow extension of memory. 📊 The tradeoff is brutal: one token every 32.7 seconds. That's not production-ready, but it's a structural blueprint for ultra-low-cost inference infrastructure.

The bigger signal is direction. 📉 As hardware bottlenecks force creative engineering, efficiency becomes the next narrative. Are we building the plumbing for the next wave of decentralized AI? 💬

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #MoE #OpenSource #Crypto

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阶跃星辰开源Step 3.7 Flash：198B参数MoE大模型，主打生产级Agent

阶跃星辰正式发布并开源新一代Flash大模型Step 3.7 Flash，采用Apache 2.0协议。模型采用196B语言主干+1.8B视觉Transformer组成的稀疏MoE架构，总参数198B，激活仅11B。支持256K上下文和3档推理，优化了生产级Agent、代码、联网搜索与多模态工作流。

为什么重要：中国AI团队在开源多模态MoE大模型领域实现重要突破，低激活参数+高能力密度的架构设计代表了高效推理的产业方向。

#AI #开源 #大模型 #MoE #人工智能

$KIMI K3 CRAMS 2.78T PARAMETERS INTO 8GB RAM — PURE CPU, NO GPU! ⚡

That 176KB C99 script making headlines? It streams Kimi K3's 1.56TB of weights off NVMe instead of holding them in memory. 🔍 Classic MoE sparse activation — only 16 of 896 experts per layer actually fire. 💡

It's a liquidity sweep in reverse: the system pulls weights on demand like a trader pulling orders off the book. 🦈 Cost? 32.7 seconds per token. That's a prototype, not production — the dev says so himself.

But for AI-crypto watchers, this is a compass. If inference can run on 8GB with disk streaming, compute costs stop being a bottleneck — and that's a narrative shift. 📊 Which AI infrastructure play rides that wave first? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #MoE #Innovation #CryptoAI

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