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OpenRouter tests free Ox Alpha with a 1M-token context window

OpenRouter is testing Ox Alpha, a free stealth model with a 1M-token context window. The model accepts text, image, and video inputs and is offered with zero data retention during the test.

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OpenRouter tests free Ox Alpha with a 1M-token context window
OpenRouter tests free Ox Alpha with a 1M-token context window

TL;DR

  • Ox Alpha is a free OpenRouter stealth preview with a 1M-token context window and text, image, and video input, as OpenRouter's launch post describes.
  • The data-policy claims differ: opencode's launch post called the test zero data retention, while OpenRouter's privacy note said the provider does not train on prompts or completions; the current model page says the provider retains both.
  • The anonymous provider has exposed stealth/ox-alpha through OpenAI-compatible and Anthropic-compatible APIs, with tools, structured output, and reasoning controls documented on OpenRouter's listing.
  • A small DeepSWE sample from davis7 put Ox Alpha at 80% across 10 tasks, ahead of the poster's 65% Fable and 52% GPT-5.6-sol runs.

The model listing gives the preview a 131,072-token output cap. Hermes Agent added it immediately, while a LocalLLaMA post turned the missing provider name into the first community investigation.

API surface

OpenRouter exposes Ox Alpha as stealth/ox-alpha. Its quick-start documentation uses the standard OpenAI-compatible endpoint, while the model listing also documents Responses and Anthropic Messages interfaces.

The documented contract is unusually expansive for a free stealth test:

  • Context: 1,048,576 tokens, with a 131,072-token maximum output.
  • Modalities: text, images, and video in; text out.
  • Controls: reasoning, max_tokens, temperature, top_p, top_k, tools, tool_choice, and response_format.
  • Reasoning continuity: OpenRouter says clients can pass the complete reasoning_details array back on later turns.

Data handling

The privacy language is the material caveat. opencode's launch post advertised “Zero Data Retention,” and OpenRouter's follow-up says the provider does not train on prompts or completions.

The current Ox Alpha page says prompts and completions are retained by the anonymous third-party provider and are not used for training. The listing supplies no retention period, and says OpenRouter routes requests rather than operating the model.

The anonymous provider

OpenRouter identifies the developer only as a third-party provider that chose to remain anonymous during the preview. The provider question also anchored a LocalLLaMA post shortly after the model appeared.

AiBattle_ first floated a Xiaomi MiMo connection from a token behavior comparison and Xiaomi's earlier anonymous OpenRouter tests. A later follow-up instead relayed unverified reports of GLM-like tokenizer behavior and error messages. Neither OpenRouter nor a model developer has attached a name to Ox Alpha.

DeepSWE sample

davis7 ran Ox Alpha through 10 DeepSWE tasks and reported 80%, with the explicit warning that such a small subset could have substantial variance.

The table records eight passes and two misses, versus the same poster's 65% for Fable, 62% for GLM-5.3 and Grok 4.6, and 52% for GPT-5.6-sol. It is an early smoke test, not a published benchmark result.

Free week and Hermes Agent

opencode described the offer as free for the next week, with generous rate limits, near-unlimited usage, and 100T tokens per day of claimed capacity.

OpenRouter's listing currently prices input and output at $0. Teknium said Ox Alpha was added to Hermes Agent through opencode and OpenRouter, giving the preview an immediate agent surface as well as direct API access.

Further reading

Discussion across the web

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