Databricks benchmarked the Chinese open-source model GLM 5.2 on its own multi-million-line codebase and found it statistically tied with Anthropic's Opus 4.8 at lower cost, making it the company's default coding engine. GLM 5.2 hit the top performance cluster at $1.28 per task versus $1.94 for Opus. Databricks now plans to make it a daily workhorse for its developers, citing developer feedback from internal pilots. Coinbase moved to Chinese models including GLM-5.2 and Kimi 2.7, cutting AI spending in half while token usage kept climbing. Lindy ditched Claude entirely for Deepseek v4 and saved millions. Snowflake tested GLM-5.2 against Opus 4.7 and found them nearly tied at a fraction of the cost. On OpenRouter, Chinese models have topped 30 percent of weekly traffic since February 2026, up from 11 percent last year, at 60 to 90 percent lower cost than Western alternatives. Databricks' analysis through Unity AI Gateway found that 61 percent of coding tasks from Databricks engineers are medium complexity, about 19 percent low, and only 12 percent high. The company plans to route more work to cheaper tiers based on task complexity. Databricks notes that token price and actual task cost are not the same, as token efficiency varies widely by software environment.