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9. Execution and Performance - Execution Modes and Performance Targets

9.1 Mode 1 — Single Node

  • Semantic Core only.
  • Fast.
  • Minimal overhead.

9.2 Mode 2 — ELM-Assisted Mode

  • Semantic Core + one or more role-based or domain-specific experts.
  • Typically sequential or lightly parallel execution.
  • Used when specialist assistance improves quality without full swarm overhead.

9.3 Mode 3 — Swarm Mode

  • Multiple nodes execute.
  • Weighted consensus or arbiter-mediated synthesis.
  • Reputation-based selection.

9.4 Mode 4 — Agent Mode

  • Multi-step execution involving memory, grounding, verification, and optional tool use.
  • Secure tool path enforced through the Tool Intermediary.
  • Used for higher-complexity workflows.

9.5 Execution Strategy Principles

  • Local-first, distributed-second: Execute locally when possible and escalate only when justified.
  • Small effective cognitive sets: Select the smallest effective set of ELMs and services rather than activating a large swarm by default.
  • Roles over raw scale: Prefer assigning the right expert role over scaling one model indiscriminately.

10 Performance Targets

Metric

Target

Tokens/sec

≥ INT4 baseline where comparable

Memory usage

≤ practical low-bit deployment envelope

Grounded quality

≥ baseline single-model factual reliability

Verification / formatting quality

measurable improvement

Multi-node scaling

near-linear up to initial swarm targets where network conditions permit

Tool safety overhead

bounded and separately reported from inference latency

Customization efficiency

choose the lowest-cost path among retrieval, memory, private ELM invocation, and swarm consensus that still satisfies quality and policy requirements