Databricks, Claude 대신 GLM 채택 — 34% 저렴한 비용으로 Opus에 필적
databricks는 내부 벤치마크에서 태스크당 $1.28로 anthropic의 opus 4.8($1.94)에 필적한 뒤 glm 5.2를 기본 코딩 모델로 채택했으며, 이는 프로덕션 환경에서 중국 오픈소스 대안으로의 전환을 시사합니다.
databricks switched its default coding engine to glm 5.2, finding it statistically tied with anthropic's opus 4.8 at $1.28 per task compared to opus's $1.94, and now routes work by complexity to optimize the pareto frontier of price and performance. internal tests showed top-tier models from openai, anthropic, and open source achieving 82-90% pass rates, but extreme cost disparities—often 60-90% lower for chinese models—are driving western enterprises like databricks, coinbase, and lindy to defect from proprietary incumbents. this validates that open-source models are production-grade and suggests future engineering stacks will dynamically route tasks across a fragmented vendor landscape based on real-time cost-to-quality metrics rather than a single flagship provider.