Databricks dumps Claude for GLM — and matched Opus for 34% less
databricks adopted glm 5.2 as its default coding model after it matched anthropic's opus 4.8 in internal benchmarks at $1.28 versus $1.94 per task, signaling a shift toward chinese open-source alternatives in production environments.
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.