Hey Product Hunt 👋 I built APIMaster.ai after getting tired of not knowing whether the "Claude Opus" I was paying for was actually Claude Opus. The obvious check — asking the model "what are you?" — is trivially fakeable. Any reseller can patch a system prompt to make GPT-3.5 swear it's Opus. So I built something that doesn't ask. It measures. The tool probes behavioral signatures: token-level decision patterns under ambiguity, response structure preferences, characteristic failure modes on adversarial inputs with noise injection. These survive system prompt overrides. To fake them convincingly, you'd have to actually run the real model — which defeats the whole point of cheating. What the data showed on day 1 (from r/SillyTavernAI, 19K views): ✅ Verified: api.navy (97%), nano-gpt.com (84%), openrouter.ai (84.7%), pi.tokenator.cloud (78%) 🔴 Fraud: api.airforce — serves GPT 5.4 at 100% confidence regardless of what model you request (Opus, Sonnet, Gemini — all GPT 5.4) 🟠 Suspicious: 9 out of 9 "cheap Opus" endpoints in my original batch — all showing probability mass leaking into haiku-4-5, deepseek-v4-flash, and other cheaper models The tool is free, MIT licensed, no API key storage (use a throwaway key anyway — that's good hygiene with any third-party tool, including this one). Happy to answer questions about the methodology — especially skeptical ones. The code is open if you want to audit it. Cheap != Cheat. But verify before you trust.

APIMaster.ai

Detect fake LLM APIs & reveal the real model underneath

Detect fake LLM APIs & reveal the real model underneath