vLLM-iOS: 88% Faster Multi-Agent Inference on iOS
SMRTR summary
A developer built vLLM-iOS, a native Swift port of vLLM's continuous batching system for iPhones, achieving 88% faster multi-agent inference than llama.cpp at 8 concurrent streams. By sharing a single weight read per token across all agents and reusing cached prompt prefixes, the engine runs 16 research tasks in 25 seconds within one thermal budget, compared to llama.cpp's 47 seconds for half as many requests.
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