LatentPort: Beyond KV Cache - Cross-Model Transfer of Recurrent Memory in Hybrid Language Models: A 4B-to-9B Hybrid-State Handoff Without Target Prefix Replay
First demonstrated cross-model handoff of persistent recurrent inference state between Qwen3.5 4B and 9B hybrid models without target prefix replay.
LatentPort demonstrates persistent hybrid-state transfer from a Qwen3.5 4B model to a 9B sibling without the receiver rereading context, claimed as the first cross-model handoff of recurrent inference state without target prefix replay. Adding the Gated DeltaNet persistent-state package to translated attention KV lowers teacher-forced NLL by 0.747 nats/token, improving all 64 PG19 documents. A 434,176-parameter correction yields 0.076 nats/token excess NLL versus native 9B, JS divergence 0.022, and native context recovery of 0.918, though evidence covers only one direction, one geometry-matched pair, and 4K teacher-forced continuation.
- First 4B-to-9B recurrent-state handoff with zero target prefix tokens processed
- GDN persistent-state package cuts NLL 0.747 nats/token across 64 PG19 documents
- Corrected 9B reaches 0.076 nats/token excess NLL, 0.918 native context recovery
- Scope limited: one direction, one model pair, 4K continuation, 16K untested
From the original article
1 min read at huggingface.co
Can one language model hand its live memory to another without the receiver rereading the context? We demonstrate useful persistent hybrid-state transfer across one architecture-matched Qwen3. 5 4B-to-9B sibling pair.
By Simon P. Villani · huggingface.co
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