What is the fastest CPU-only architecture for a lightweight tool-using agent?
Objective-Good310 · reddit · 2026-07-21
A Reddit user is looking for the fastest CPU-friendly architecture for a lightweight agentic assistant.
- Target use case: web search, tool calling, and basic RAG on an Intel i7-8650U with 16 GB RAM and no dGPU.
- They care more about prefill and decode speed than raw intelligence, because the assistant will do short back-and-forth tool loops.
- Models already tried include BitNet b1.58-2B-4T and LFM2.
- They observed LFM2’s prefill getting slower as the conversation grows, and wonder whether that is a caching issue in llama.cpp/Ollama or something inherent to the architecture.
- They are asking for architectures that stay fast with longer context, especially pure SSM or linear-attention options like Mamba2 or RWKV-7, plus models that support native function calling at small sizes.
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