Hi, I’m curious how people here actually choose models in practice.
We’re a small research team at the University of Michigan studying real-world LLM evaluation workflows for our capstone project.
We’re trying to understand what actually happens when you:
• Decide which model to ship
• Balance cost, latency, output quality, and memory
• Deal with benchmarks that don’t match production
• Handle conflicting signals (metrics vs gut feeling)
• Figure out what ultimately drives the final decision
If you’ve compared multiple LLM models in a real project (product, development, research, or serious build), we’d really value your input.
Short, anonymous survey (~5–8 minutes):