🔥36氪•Stalecollected in 5m
Xiaomi MiMo-V2.5 Achieves Five Core Technical Breakthroughs
💡Learn how Xiaomi optimized LLM inference to achieve permanent API price cuts without sacrificing margins.
⚡ 30-Second TL;DR
What Changed
Implemented KVCache dual-pool and GCache distributed caching
Why It Matters
The efficiency gains in MiMo-V2.5 demonstrate how infrastructure optimization can drive down costs for LLM deployment. This sets a competitive benchmark for other model providers in the Chinese market.
What To Do Next
Evaluate the MiMo-V2.5 API for your production workloads to leverage the new cost-efficiency and performance improvements.
Who should care:Developers & AI Engineers
Key Points
- •Implemented KVCache dual-pool and GCache distributed caching
- •Optimized Decode stage with MTP acceleration
- •Maintains profitability despite permanent API price cuts
- •Distributed 100 trillion free tokens to developers
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Original source: 36氪 ↗