DeepSeek Sparse Attention

NaiveAI released Naive-N0.5-Flash, an open-weight 309B mixture-of-experts model with 15.5B active parameters, native 1M-token context, and no full-attention layers, built for coding and AI R&D. The mo…

Researchers from Tsinghua University and Z.ai have proposed IndexCache, a method to reduce the computational cost of DeepSeek Sparse Attention (DSA) in GLM-5.2. IndexCache exploits the observation tha…

Local large language models have nearly caught up to frontier models for everyday tasks as of mid-2026, driven by engineering advances in sparse attention and mixture-of-experts architectures that red…