LLM Status vs Marginal

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

Track every LLM call's cost and slice it by customer, feature, model, any field you define.

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 Marginal

Track every LLM call's cost and slice it by customer, feature, model, any field you define. Marginal tracks the cost of every LLM call and slices it by the fields you care about, customer, feature, model. Cost is computed server-side, usage in, dollars out. Every API request is logged with its outcome, accepted counts, rejected events and why, stripped keys, unpriced models. The SDKs are zero-dependency, buffered, fire-and-forget: track() never throws and never blocks your request path.