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The local bar for Hy Memory just dropped.
Size: 60 GB to 18 GB.
Stack: vLLM to one llama.cpp binary.
Quality: Q6_K 58.8%, Q4_K_M 56.5% on our LoCoMo eval.
Your memory bank stays on your disk.
🤗
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A 3B active model beats Opus 5 at memory. We open-sourced the full stack — model, engine, and app.
Hy Memory handles chat, work, and code memory in one layer, and it's first on all four benchmarks we ran, leading MemoryArena by 10.2 points while cutting memory volume 51.8% and recall tokens 39.3%.
The model isn't tied to our engine. Drop Hy-Memory-30B-A3B into Mem0, MemOS, or EverMemOS and it still comes out on top, even on the one system it never trained on. It's already running in our own products, where one assistant's multi-hop recall went from 50% to 90%. It also unifies memory across Codex, Cursor, WorkBuddy, and more.
Repo:
Weights:
Questions welcome in the replies.
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