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Benchmarking when agent orchestration is worth its inference cost under latency, cost, and accuracy trade-offs.

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inference-aware-agents (V1)

Python benchmark framework comparing agent orchestration architectures on synthetic tasks only.

Scope V1 (frozen):

  • synthetic benchmark only
  • no real GPU integration
  • no web UI
  • no distributed runtime
  • no real vLLM dependency
  • proxy-based inference cost/latency/context modeling only
  • focus on orchestration, evals, and ablations

Entry points (after you run pip install -e .):

  • Run benchmark: python scripts/run_benchmark.py --config configs/experiment_v1.json
  • Aggregate results: python scripts/aggregate_results.py --traces-dir ./outputs/traces

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Benchmarking when agent orchestration is worth its inference cost under latency, cost, and accuracy trade-offs.

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