The problem with AI model advice
Every week there's a new “best model” thread on X. Every benchmark is gamed. Every comparison is sponsored. Meanwhile, you just need to know what actually works.
X is all hype, no signal
Every model launch triggers a wave of takes from people who haven't shipped anything with it. Benchmarks get cherry-picked. Hot takes get engagement. Practitioners get noise.
Leaderboards are pay-to-play
“Best AI model” lists are sponsored content disguised as reviews. The models at the top paid to be there. You deserve rankings backed by real usage, not ad budgets.
Real answers are buried in DMs
The best model advice comes from practitioners you know — in Slack threads, DMs, and team stand-ups. ModelMix.ing makes that knowledge public and searchable.
Built different
ModelMix.ing is for practitioners, by practitioners. Every stack is from someone who actually uses these models daily.
Community-driven
Real people sharing what they actually run in production. Upvotes from practitioners, not bots.
Zero sponsors
No model provider pays to be ranked higher. No affiliate links. No hidden incentives. Ever.
Full context
Not just “best model” — see the whole stack. Use case, budget, hardware, orchestrator, and why.
How it works
Share your stack
List the models you use, what role each plays, your budget tier, and your hardware. Takes 60 seconds.
Community validates
Other practitioners upvote stacks they've tried. “I run this too” signals real adoption, not theoretical approval.
Signal rises, noise fades
Filter by use case, budget, or hardware. Find the stack that matches your constraints — not someone else's marketing budget.
“We got tired of asking the same question in every Discord, Slack, and X thread: what models are you actually using? So we built the place where the answer lives.”
— The ModelMix.ing team
Join the practitioners
Stop guessing which models to use. See what the people building real things actually run.