Open LLM Deploy

Agent harness and benchmark scrutiny accelerates

Agent harness and benchmark scrutiny accelerates

Harness-Zero reports a jump from 23.3% to 44.3% by distilling harness behavior into a Qwen3.5-9B-based system. WhatWorkedBench, repository transformations, SWE-FLUX, Qwen-Planner-Agent, Agent-Editing World Model, and recent NVIDIA NIM guidance reinforce that execution access, context structure, task design, token budgets, workload traces, and serving configuration can substantially change apparent agent and coding performance.

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Updated Sep 25, 2026