CacheBridge transfers KV caches across different model architectures

CacheBridge (arXiv 2609.00891, Wed 2 Sep digest) avoids shared-prefix replay when routing requests between LLMs: it co-designs architecture-indexed mapper support, attention-aligned calibration, and bounded mapper construction while retaining a closed-form affine-mapper interface that translates source-model KV caches into target-model caches online. It improves on Full-Head Mapping, whose per-head-from-every-head design is sensitive to architectural differences and whose mapper cost grows with layer support. The same window carries an independent companion: 'A Universal Context-Reuse Layer for Cross-Model KV Sharing' (2608.30963, Tue 1 Sep digest), which studies cross-model KV translation across differences in scale, architecture, attention configuration, tokenizer, and model family.

Multi-model pipelines (router -> small model, draft -> verifier, generalist -> specialist) currently pay full prefill on every handoff, which dominates cost exactly where routing is supposed to save money. Two independent groups publishing cross-model KV transfer in the same window suggests the assumption 'KV caches are model-specific' is starting to bend; teams running model-routing stacks should track this the way they tracked prompt caching in 2025.