Raycast AI - Which models are you using?

@fmerian I typically choose models based on the complexity and nature of the task. When working with large codebases, especially when I need to refactor or modify a section that has downstream effects, Grok-3 performs exceptionally well. Instead of manually tracing dependencies and debugging ripple effects, I often pass the entire file to Grok-3 and let it regenerate a consistent version. This saves significant time and reduces potential bugs. If something in Grok-3’s output doesn’t work as expected, I switch to ChatGPT-4o to quickly analyze the issue and identify what went wrong. Once I have a working fix, I pass the updated logic back to Grok-3, and it regenerates the full file with the fix integrated. That way, I avoid spending 10 to 15 minutes manually editing the file, Grok-3 usually handles it in a minute or two. For real-time information or fast web-based insights, I rely on Perplexity. Each model plays a specific role in my workflow depending on the task and requirements.