오픈 웨이트 + 사유 데이터가 나오기 전까지 최첨단 모델들은 금융 테스트에 실패
파인튜닝된 qwen3-235b가 14배 낮은 비용으로 Bridgewater의 금융 분석 과제에서 gpt와 claude를 능가하며, 사유 데이터가 진짜 해자(moat)임을 증명했습니다.
bridgewater and thinking machines lab fine-tuned the open-weight qwen3-235b model on internal financial data, achieving 84.7% accuracy on document triage tasks compared to 78.2% for top proprietary models. the project highlighted that frontier models like gpt and claude failed to meet the 80% deployment threshold because the necessary 'judgment' data exists only in private corporate archives, not public training sets. the fine-tuned model operates at nearly 14 times lower cost than commercial alternatives, offering a blueprint for companies to build competitive ai without sharing sensitive trade secrets with large labs.