1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AR2026
Full-Pipeline Inference Optimization for MiMo-V2.5 Series: Pushing Hybrid SWA Efficiency to the Limit
Xiaomi MiMo Team, Anqi Liu, Aoxin Ma +28
We present a full-pipeline inference optimization for the MiMo-V2.5 model family, which combines Hybrid Sliding Window Attention (Hybrid SWA), sparse Mixture-of-Experts (MoE), and…
cs.CL2026★ 1 cited
MiMo-V2-Flash Technical Report
Core Team, Bangjun Xiao, Bingquan Xia +123
We present MiMo-V2-Flash, a Mixture-of-Experts (MoE) model with 309B total parameters and 15B active parameters, designed for fast, strong reasoning and agentic capabilities. MiMo-…
cs.DC2025
HydraServe: Minimizing Cold Start Latency for Serverless LLM Serving in Public Clouds
Chiheng Lou, Sheng Qi, Chao Jin +5
With the proliferation of large language model (LLM) variants, developers are turning to serverless computing for cost-efficient LLM deployment. However, public cloud providers oft…