Z.ai claims Ox Alpha after five days of guessing

Ox Alpha showed up on OpenRouter over the weekend with no listed creator. Usage more than doubled DeepSeek's within days, making it the platform's biggest launch with no name attached.

The mystery drew a crowd. A DeepMind researcher guessed Gemini. A browser-based fingerprinting tool pointed at the GLM family at six of nine probes.

On August 26, Z.ai told Bloomberg it built Ox Alpha as a new GLM-series iteration, with open weights going out tonight. On OpenRouter it's listed as stealth/ox-alpha, a reasoning model for coding and agentic work with a 1,048,576-token context window. Pricing for prompts and completions is zero, and it takes text, image and video input.

The number I trust here comes from a repo test, not a leaderboard score. Cline ran Ox Alpha and Fable on the same bug from its own codebase, and both fixed it. Ox Alpha used far fewer thinking tokens to get there.

Cline's test thread noted that Fable announced it had found the root cause seven separate times before it acted on the fix. That's a measured cost difference from real use.

Don't take fewer reasoning loops as proof of better reasoning. A thread on r/singularity raised the fair objection that committing to a first conclusion faster can also mean skipping edge cases.

The "80% coding score" that circulated last week dropped to 58.4% once someone ran the full evaluation. Any single number tied to this model deserves a second look once the weights are public.

If the weights ship tonight as promised, this becomes the cheapest way to test long-context agentic workflows. The free OpenRouter listing and million-token context remove the cost excuse most people have used to skip that test. Pin the exact model string before you test, since free stealth listings on OpenRouter don't usually stay free.