Model Card: Hy-Memory-30B-A3B
Hy-Memory-30B-A3B: open-sourced 2026-10-15 under Apache-2.0, a 30B-total / ~3B-active MoE with a 262,144-token context window, trained specifically to run the "write" path inside agent memory frameworks (Mem0, MemOS, Hy-Memory). Two-stage training — On-Policy Distillation plus Attributed Memory RL — raised the cross-harness macro average from 47.66 (its own base model) to 55.49, which Tencent frames as beating Claude Opus 5's 54.62. Broken down, though, the Mem0/Hy-Memory/MemOS margins are all under 0.6 points — essentially statistical noise — and the real gap comes from the single held-out EverMemOS harness (56.89 vs. 54.04, a 2.85-point difference), which accounts for over 80% of the overall lead. There's no quantized build and no hosted API yet, and the companion MemHub desktop app's install path isn't working end to end.