fascinating data from @cline users on grok-code-fast-1 context: "sonic" was @xAI's stealth model that we released to Cline users a few weeks ago. the feedback was honestly not great. tool use errors, reasoning issues, general unreliability. fast forward to this week and the sentiment has completely flipped. users are saying grok-code-fast "feels like an entirely different model than the sonic I was testing" and "better than gpt5-mini " the technical improvements are notable: >major reduction in tool calling errors >better reasoning capabilities for planning mode successful complex database migrations ("oddly painless" schema changes) reliable code generation with fewer iterations particularly strong with Go programming but here's what's most interesting: users are actively switching FROM gpt-5-mini TO grok because of superior performance. one user noted "wayyyyyyy less tool use errors than Sonic which is the biggest change" another called it "on par with sonnet 3.5" while being "extraordinarily fast", maintaining quality while delivering speed. it should be noted that sonnet 3.5 is still a really good model. the free access (extended to Sept 10) is driving rapid adoption, but the long term pricing for a model of this quality is positionally notable: $0.20 per million input tokens and $1.50 per million output tokens this positions grok-code-fast as potentially the most cost-effective frontier-class coding model even when the free period ends. the Sonic to Grok transformation demonstrates how valuable Cline's complex tool usage, massive context ingestion, and diff editing data is for training frontier coding models.