QKVShare: Quantized KV-Cache Handoff for Multi-Agent On-Device LLMs
Multi-agent LLM systems on edge devices need to hand off latent context efficiently, but the practical choices today are expensive re-prefill or full-precision KV transfer. We study QKVShare, a framework for quantized KV-cache handoff between agents that combines token-level mixed-precision allocation, a self-contained CacheCard representation, and a HuggingFace-compatible cache injection path. Our current results support a narrower but clearer story than the original draft: on 150 GSM8K problems with Llama-3.1-8B-Instruct, adaptive quantization remains competitive under repeated handoff and shows its clearest gains against uniform quantization in deeper-hop, higher budget settings; for h...
| Authors | Pratik Honavar, Tejpratap GVSL |
|---|---|
| Primary category | cs.AI |
| Published | 5 May 2026 |
| Last updated at source | 5 May 2026 |
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