Anonymous Model Ox Alpha Tops OpenRouter: 95/95 Tokenizer Fingerprint Points to Zhipu's GLM

Forum topic · QianXun · 2026-08-24

Summary

Ox Alpha, an anonymous model listed under the 'stealth' provider on OpenRouter, reached the #1 spot on August 22, 2025, ending DeepSeek's 56-day streak and reportedly handling over 4 trillion tokens in daily calls from top clients like Claude Code and Hermes Agent. The model offers a 1M-token context window, 131K max output, multimodal input (text, image, video), forced reasoning mode, and a claimed 100T tokens/day free capacity via OpenCode ending around August 26. Community forensics strongly point to Zhipu AI as the origin: researcher Joseph W. Elstner matched Ox Alpha's prompt_tokens against GLM-5's tokenizer in 95/95 probe tests with zero MAE (plus a constant +75 offset from a hidden system prompt), while video token-budget tests matched GLM-5V-Turbo. A malformed-request experiment returned a Java stack trace referencing com.wd.paas classes used in Zhipu's bigmodel.cn and api.z.ai APIs, and error code 1214 matched Z.ai-hosted GLM models—though DeepInfra-hosted GLM weights returned different errors, proving the fingerprint is service-layer, not weights. Benchmarks are mixed: a viral 10-question DeepSWE test showed 80% pass, but the full 113-question run yielded ~63%. Zhipu and Google have not officially claimed the model.

Key points

Ox Alpha appeared anonymously on OpenRouter (provider: "stealth") on August 20, 2025, and hit #1 on August 22, ending DeepSeek's 56-day streak on OpenCode. Chinese communities nicknamed it 「Ox」 ("the bull is here" meme). Stripe CEO Patrick Collison called it "very impressive."
Specs: 1,048,576-token context window, 131,072 max output tokens, multimodal input (text, image, video), forced reasoning mode with efforts max/high/low (default max), temperature=1, top_p=0.95, fixed top_k. OpenCode claims 100T tokens/day preview capacity (unaudited), with nearly unlimited free usage on OpenCode Go through ~August 26.
Usage: OpenRouter 8/23 data showed top five callers (Hermes Agent, Claude Code, etc.) exceeded 4 trillion tokens cumulatively; OpenCode reported ~250B tokens, ~8,500 unique users, 110K+ sessions.

Tokenizer fingerprinting: 95/95 match with GLM-5

Researcher Joseph W. Elstner fed 95 probe strings (ASCII, Python, CJK, emoji, Arabic, Hebrew, Thai, rare Unicode, whitespace, regex, HTML, JSON, long repeats) to Ox Alpha and compared usage.prompt_tokens against 14 mainstream models.

Aug 23 retest against Zhipu's published GLM-5 vocabulary: 95/95 exact matches, MAE 0.0.
Relationship: Ox Alpha prompt_tokens = GLM-5.3 prompt_tokens + 75 (constant offset, explainable by a hidden system prompt wrapping the chat template).
Chetaslua's controlled video tests (frame rate, duration, resolution) matched GLM-5V-Turbo on four metrics (~147 tokens/second growth, frame sampling independent of duration, per-frame resolution token scaling); MiMo, Qwen, and GLM-4.6V were ruled out.

Service-layer fingerprint: Z.ai

A malformed request (top_p set to string "abc") returned a Java stack trace containing com.wd.paas.api.domain.v4.chat.ChatCompletionRequest — matching Zhipu's official API structure on open.bigmodel.cn and api.z.ai.
A bad-role test triggered error code 1214, identical to Z.ai-hosted GLM models.
Control: the same GLM-5.2 weights hosted on DeepInfra returned a different error format — so the fingerprint identifies the serving layer, not the weights. Chetaslua's confidence: 0.98.

Benchmarks: mixed reality

A viral 10-question DeepSWE community test showed 80% pass (vs. Fable 5 at 65%, GLM-5.3 at 62%, GPT-5.6 Sol at 52%).
The full 113-question run by developer Ben Davis scored ~63% — he noted the 10-question sample's variance was misleading. Ox Alpha was not yet on the public BenchSift leaderboard as of 8/21.
Abacus.AI CEO Bindu Reddy said results were below expectations on some metrics; Ethan Mollick was underwhelmed. Weaker at low reasoning effort and clearly behind Gemini on vision tasks.
Real signal: production agent tools (Claude Code, Hermes Agent) drove 18B+ tokens of real consumption.

Identity candidates and privacy terms

Zhipu (leading): tokenizer match, Java class path, code 1214, naming lineage (Pony Alpha → Ox Alpha).
Google (trailing): a DeepMind researcher replied "Gemini"; 1M context and multimodal fit Gemini's roadmap.
Third-party hosting (minority): Microsoft MAI family or Cursor training their own.

OpenRouter terms: the anonymous provider retains prompts and completions but does not use them for training. Neither Zhipu nor Google had claimed the model as of Aug 24.

Takeaways

1. Model lineage is now community-verifiable — tokenizer fingerprints and service-layer stack traces make anonymity untenable. 2. "Where a model is trained" and "where it is deployed" are separate questions; the GLM vocabulary + Z.ai serving stack combination is replicable across vendors. 3. For practitioners: test Ox Alpha before the ~Aug 26 free window closes, avoid locking core agent paths to a single closed API, and evaluate retention/training terms of anonymous providers.

Sources

Implicator.ai — "Ox Alpha Matches Zhipu's GLM Tokenizer in 95 of 95 Tests" (Joseph W. Elstner, 8/22–23)
Singularity.Kiwi — "An Anonymous AI Model Appeared on OpenRouter. The Trail Points to Zhipu." (Chetaslua)
NetEase / QbitAI / Zhitong Caijing coverage (8/24)
Reddit r/singularity discussions; OpenRouter model list 8/23; OpenCode Zen docs (100T tokens/day claim)