LLM Status vs Wattfare

Track where every AI model is used across your apps, and get warned before one is deprecated or retired.

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you.

About LLM Status

Track where every AI model is used across your apps, and get warned before one is deprecated or retired. Run mm for the full terminal dashboard: it scans the current repo on launch, then you arrow through every model it calls, browse the registry, and see what's new, live. Both pull the signed registry from cdn.llmstatus.ai once, then run offline. The Here and What's New tabs read straight off the signed registry, no account, works offline.

About Wattfare

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you. OpenAI-compatible Works with the Vercel AI SDK ~5-min integration. One button connects a user's inference budget to your app, metered, capped, and revocable. The problem AI costs are the one line item you can't predict. Every AI app makes the same uncomfortable bet: price high enough to survive your power users, ration usage so nobody hurts you, or quietly lose money on the heavy ones.