Xiaomi MiMo's Long-Context Inference Optimization in Practice
burny_tech · x · 2026-07-19
This piece explores how a hybrid Sliding Window Attention (SWA) mechanism can drastically reduce the cost of long-context inference in production environments, showcasing the specific engineering implementation using Xiaomi's MiMo-V2.5 model as an example.
The core optimization lies in restructuring the KV Cache system so that SWA only retains the recent window instead of the full context, while safely reusing prefixes across requests. Combined with better cache routing, distributed caching, and multimodal preprocessing, it ultimately achieved:
- 93%+ KV cache hit rate
- Prefill speed increased by approximately 40%
- Decoding KV capacity expanded by about 5x
- Encoder throughput doubled (2x)
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