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Zero-Copy Context Bridging Gateway for Multi-Agent GPU Inference. Bypasses the expensive prefill phase by dynamically stitching KV Caches at the memory level using PagedAttention. Cuts TTFT latency by up to 25x and saves 40%+ VRAM for collaborative LLM workflows.

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MemStitch – Zero-copy context bridging for vLLM (25x TTFT speedup)

Name: MemStitch – Zero-copy context bridging for vLLM (25x TTFT speedup)
Availability: InStock
Author: daqulalin

by daqulalin·Jul 14, 2026·11 points·1 comment

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AI Analysis

●●●BangerWizardryBig BrainNiche Gem

25x TTFT speedup by skipping prefill via direct GPU memory stitching.

Strengths

•Context topological hashing maps prompt segments to Merkle-chain fingerprints for block matching.
•Zero-copy block stitching redirects logical attention tables to physical GPU addresses without duplication.
•Real-time developer portal visualizes physical cache block states and security alarms live.

Weaknesses

•Zero forks and stars suggest early stage; production stability unproven at scale.
•Tightly coupled to vLLM's PagedAttention; porting to TGI or other engines unclear.