Nvidia's SoL-Pi system cuts coding agent token usage nearly in half by optimizing the harness
49% token cut. Nvidia's SoL-Pi optimizes the control layer between coding agents and their environment—concrete gains for teams running agents at scale.
Why it matters
Nvidia published a system that reduces token spend for coding agents by up to 49% by refining the harness (the instructions and control flow between model and tooling) rather than the model itself. This is actionable for enterprises running agentic coding workflows where token cost is a material line item.
The key facts
6 to knowToken usage reduced by up to 49% on coding agent benchmarks
System name: SoL-Pi (optimization of control layer/harness)
Research methodology: 152 approaches tested across 3,000+ runs
Gains smaller on other benchmarks (specific benchmarks not named)
No stated performance degradation on primary benchmark
Optimization target: control layer between model and environment, not the model weights
Go to the source
The Decoderthe-decoder.com
Publisher excerpt: SoL-Pi cuts coding agents' token usage by up to 49 percent with little change in performance by optimizing the control layer between the model and its environment. A research agent tested 152 approaches across more than 3,000 runs to develop the system, though the gains were smaller on other…