@dair_ai
NEW paper worth reading. GPT-5.4 nano plus a critic-comparator orchestration loop hits 76.4% on SWE-bench Verified, matching standalone Gemini 3 Pro and Claude Opus 4.5 Thinking. The trick is to select from k=8 weak-model proposals using execution and proof signals. What does this mean? Many of the patches you'd expect from a frontier model are already inside a weak model's top-8 candidates. When you have 8 candidate patches from a weak model, don't ask the model which is best. Run them and verify them. That's enough to match a frontier model's accuracy. The takeaway for AI devs: a weak model's top-k often already contains the right answer. What limits you is the quality of your selector, not the capability of the model. Paper: https://t.co/Gx7j7EP9BM Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c