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LoopCoder-v2 Parallel Loop Transformer architecture overview diagram

LoopCoder-v2: Only Loop Once for Efficient Test-Time Computation Scaling

By Hunter Io June 19, 2026AI

LoopCoder-v2 explores Parallel Loop Transformers for test-time computation scaling, showing that R=2 achieves 64.4 on SWE-bench Verified, surpassing models 30x larger via an optimal gain-cost loop count.

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SubQ 1.1 Small Review: Subquadratic Sparse Attention Model Delivers 64x Faster Inference

By Hunter Io June 19, 2026News, AI

SubQ 1.1 Small introduces Subquadratic Sparse Attention (SSA), achieving near-perfect retrieval at 12M tokens with 64x less compute than FlashAttention-2. A deep dive into benchmarks, architecture, and real-world implications.