Rock Matrix

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   EdgeRock-4B Opens With Fixed-Memory Long-Context Inference

   Rock Matrix, Hong Kong University of Science and Technology, Carnegie Mellon University and other teams released and open-sourced EdgeRock-4B, according to QbitAI. The Qwen3.5-4B-based model uses recurrent state, a local window and Rock Memory Anchors to keep KV Cache at 72 MiB under a 256K context, reducing it by 99.1% from the source model. In team-reported tests, it ran 512 concurrent long-inference requests on one 80GB Hopper GPU at 12,124 tokens/s and averaged an 82.9% one-pass rate on AIME 2024–2026; no independent replication was provided.

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