modelprint

One page that answers one question: who is really behind that API?

Run infrastructure probes against any OpenAI-compatible endpoint and compare the fingerprints, side by side. Plumbing does not lie; personality does.

Try it: modelprint.ai No install, no build, no server. Your API keys stay in your browser tab; every call goes from your browser straight to the provider.

Why I built this

On 21 August 2026 a stealth model called Ox Alpha appeared on OpenRouter and the whole timeline turned into a detective game. The best evidence was not in anyone's hot take. It was scattered across replies: one person compared token counts, one person read error codes, one person sent temperature 2.0 and let the upstream error speak. Each trick lived and died in a single reply.

I collected them into one tool. And the same tricks matter far beyond stealth models: two days earlier I showed that DeepSeek's API silently serves a different model under the old deepseek-chat name. Providers move models behind aliases and nothing tells you. This page is how you check.

What it found on day one

The full suspect lineup, 12 models, 9 probes each, one command:

mystery model (stealth/ox-alpha) against the crowd's guesses:

 6/9  tokenizer 4/4   z-ai/glm-5.3
 5/9  tokenizer 4/4   z-ai/glm-4.7-flash
 2/9  tokenizer 2/4   openai/gpt-5.6-luna
 2/9  tokenizer 1/4   qwen/qwen3.7-flash
 2/9  tokenizer 0/4   kimi-k3, deepseek-v4-flash, minimax-m3
 1/9  tokenizer 0/4   google/gemini-3.7-flash
 0/9  tokenizer 0/4   x-ai/grok-4.6, claude-opus-5

Only the GLM family matches all four normalized tokenizer counts. Every other lab's best is 2 of 4.

The probes

The approved registry currently contains 15 probes. These are the probes the page loads and compares:

Community batch: network forensics + capability + deep signals

Held for follow-up

Five proposals from the original community batch are not in the approved registry yet: cutoff dating, wrapper leak, reasoning trace, stream cadence, and the one-token battery. They remain follow-up ideas until they pass the project's security and determinism gates.

Telemetry probes degrade honestly when a harness lacks the signal (harness-lacks-http, headers-hidden-by-cors, logprobs-unsupported) — an honest absence beats a fake fingerprint.

Tokenizer counts are normalized against a one-character baseline, so a host's hidden template cancels out. Two hosts wrapping the same tokenizer match; raw counts never would. Every tokenizer probe also runs twice and reports unstable when a router spreads calls across different hosts, instead of reporting noise as a fingerprint.

Why no censorship or personality probes: the community ran both on Ox Alpha and reached opposite verdicts on the same day. Behaviour bends to a system prompt. Tokenizers and error handlers do not.

Write your own probe

Every probe is one file in probes/ with the same contract:

// name:        your probe name
// description: what it measures and why it identifies a lab
// author:      your-handle
// version:     1.0.0

export const meta = { id: "...", name: "...", group: "tokenizer|errors|shape",
                      why: "...", long: false, author: "...", version: "1.0.0" };

export async function probe(ctx) {
  const res = await ctx.chat({ messages: [...], max_tokens: 8 });
  return { value: res.usage.prompt_tokens };   // the comparable fingerprint
}

Copy probes/_template.js, keep the rules in its header (deterministic value, never throw, no timestamps), open a pull request. Approved probes are one line in probes/index.js, and your name goes in CONTRIBUTORS.md and on the page.

Thanks to @ItIsCuthNotCup, @pjperez and @toby-bridges, who wrote probes, fixed bugs and corrected the documentation in the first days.

Honest limits

• Through a router, some answers are the router's, not the lab's. The tool detects and labels these ("router-reported", "router-validated") and reads the upstream error body whenever the router passes it through.
• A pinned host removes routing noise; the page fetches each model's real host list and offers pinning for OpenRouter lanes.
• Matching fingerprints prove shared infrastructure, not identity. A lab can serve two different models on the same stack. Read the tokenizer rows as strong evidence about the family, not a signed confession.

Run the test suites yourself

node selftest.mjs    # no key needed: every probe against a mock harness
node smoke.mjs       # every probe against two real models, prints values
node suspects.mjs    # the full 12-model lineup, prints the ranking

selftest.mjs runs everywhere; the other two need an OpenRouter key in the environment they read.

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Built by @unclecode, author of Crawl4AI

If this is useful, follow @unclecode on X for the next tool. MIT license: use it, change it, no need to ask.