SiliconBench: Speed, Memory, and Fidelity for LLM Serving on Unified-Memory Desktops

  • 类型:arxiv
  • 标识:2609.19169
  • 链接:https://arxiv.org/abs/2609.19169
  • 主分类:llm-infra
  • 形态:method
  • TLDR:Concurrent local LLM serving on unified-memory desktops must preserve memory headroom and output fidelity, which speed-only rankings overlook. We introduce SiliconBench, which evaluates nine Apple Silicon serving engines through three lenses: speed, memory, and fidelity. We evaluate chat and agent serving on Qwen3, Qwen3.5, and Gemma 4. We use a classification task to check for quality regressions against an NVIDIA reference. DGX Spark provides a complementary serving-performance reference. Three desiderata guide interpretation: serving architecture readiness, memory discipline, and multi-node
  • 副分类:evaluation
  • 待LLM分类:否
  • 来源文件
  • /inbox/tom/_candidates/2026-09-22-rag-retrieval-reranking-candidates.json
  • /inbox/tom/_candidates/2026-09-22-agent-rag-longcontext-candidates.json