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The Agent Harness Cut Token Traffic Almost in Half
SoL-Pi matched its comparison harness while reducing recorded token traffic 44.7% to 49.0%.
Summary
SoL-Pi matched its comparison harness while reducing recorded token traffic 44.7% to 49.0%.
The SoL-Pi team scaled automated harness experiments across many environments, then retained four mechanisms covering action execution, context compaction, observation handling and delegated reading. On the 51-task EdgeBench evaluation, the resulting harness performed comparably to Pi across GPT-5.6 Sol and Opus 5 while cutting recorded token traffic by 44.7% to 49.0% and reported API cost by about one third. The savings are evaluation estimates from the tested models, prices and tasks, not a universal operating-cost guarantee.
Why it matters
SoL-Pi matched its comparison harness while reducing recorded token traffic 44.7% to 49.0%.
Limits and context
- The savings are evaluation estimates from the tested models, prices and tasks, not a universal operating-cost guarantee.
Key claims
SoL-Pi matched its comparison harness while reducing recorded token traffic 44.7% to 49.0%.
Qualification: The savings are evaluation estimates from the tested models, prices and tasks, not a universal operating-cost guarantee.
Evidence: source-2026-09-19-003
Sources
- arXiv preprint 2609.20519arXiv · primary research
Corrections
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