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Reviews and evidence

Ox Alpha · Official source · Vendor report

OpenRouter Record: Ox Alpha Specs, Availability, and Anonymous Provider

OpenRouter describes Ox Alpha as a reasoning model for coding, sustained agentic work, and production workloads, listing free access, a 1,048,576-token context, up to 131,072 output tokens, and text/image/video input; the provider is only named Stealth, the developer remains anonymous, and the page publishes no reproducible capability benchmark.

Unverified: the original source could not be rechecked. Historical figures below are not current verified results.

Official sourceVendor reportEdited 2026-09-20

Test conditions

Model/version
Ox Alpha
Source
https://openrouter.ai/stealth/ox-alpha
Collection/review
2026-09-20; the dynamic source was not reopened
Method and sample
OpenRouter describes Ox Alpha as a reasoning model for coding, sustained agentic work, and production workloads, listing free access, a 1,048,576-token context, up to 131,072 output tokens, and text/image/video input; the provider is only named Stealth, the developer remains anonymous, and the page publishes no reproducible capability benchmark.

Key data and applicable tasks

One-sentence takeaway

OpenRouter describes Ox Alpha as a reasoning model for coding, sustained agentic work, and production workloads, listing free access, a 1,048,576-token context, up to 131,072 output tokens, and text/image/video input; the provider is only named Stealth, the developer remains anonymous, and the page publishes no reproducible capability benchmark.

Test environment

  • Entry point: OpenRouter's stealth/ox-alpha model record.

  • Provider: The page shows one provider named Stealth; OpenRouter says it only routes requests and is not the developer, owner, or provider.

  • Page state: Free preview; the pricing table shows $0/M tokens for both input and output.

  • Dynamic page metrics (at collection): The provider table showed 5.78 seconds P50 latency and 24 tokens/s throughput; the page's one-week aggregate separately showed 31 tokens/s average P50 throughput and 4.44 seconds average P50 latency. These have different scopes and should not be merged into one benchmark score.

Inputs/configuration

  • Context limit: 1,048,576 tokens (about 1M).

  • Maximum output: 131,072 tokens.

  • Input modalities: Text, image, and video.

  • Positioning: A reasoning model for long-horizon software engineering, complex reasoning, and workflows combining text with visual context.

  • Not disclosed: Prompts, temperature, effort, tool harness, repeat count, task set, and failure traces are not provided on the page.

Results data

ItemVerifiable page informationInterpretation boundary
Input price$0/MCurrent preview price, not a long-term commitment
Output price$0/MCurrent preview price, not a long-term commitment
Context1,048,576 tokensCapacity limit, not proof of whole-repository recall
Maximum output131,072 tokensServer limit, not an expectation for every response
P50 latency5.78 seconds (provider table)Dynamic observation; record collection time
P50 throughput24 tokens/s (provider table)Different scope from the one-week 31 tokens/s summary
3-day availability98.78%OpenRouter service observation, not a capability benchmark

Conclusion

This is an anonymous preview route with relatively clear headline specifications but limited capability evidence. It is suitable for low-cost coding, long-context, and agent prototypes when data is non-sensitive; the 1M context, free price, or current latency alone cannot establish superiority over GPT, Claude, GLM, or other models.

The OpenRouter page says prompts and completions are retained by the provider but not used for training; it also defers other use to the Stealth Model Terms. Recheck the applicable terms before use and do not treat an anonymous preview as a privacy or availability SLA.

Limitations

  • No developer name, weights, version snapshot, or public technical report.

  • No SWE-bench, Arena, or unified-harness score is published; the current metrics are routing/service observations.

  • Latency, throughput, and availability change with time and load; live observations are not fixed performance guarantees.

  • Free access is a preview condition; future pricing, limits, and availability are unknown.

  • The page's retention statement and the general Stealth terms should be interpreted using the stricter boundary.

Reproduction steps

  1. Open stealth/ox-alpha in Tabbit and record the page date, provider, pricing, and service metrics.

  2. Use a redacted repository and fix 10–20 coding and long-context tasks, saving the full prompt, tool permissions, model ID, and response trace.

  3. Repeat at least three times and report first-pass success, post-fix tests, latency, output tokens, retries, and reviewer rework.

  4. Compare with a known-snapshot baseline using the same tasks, harness, and permissions before drawing conclusions.

What this supports

  • OpenRouter describes Ox Alpha as a reasoning model for coding, sustained agentic work, and production workloads, listing free access, a 1,048,576-token context, up to 131,072 output tokens, and text/image/video input; the provider is only named Stealth, the developer remains anonymous, and the page publishes no reproducible capability benchmark.

What this does not support

  • the source provides no matching independent retest, complete sample, or current-availability evidence for “OpenRouter Record: Ox Alpha Specs, Availability, and Anonymous Provider” (source date the source date); it cannot generalize to every client, task, or production guarantee.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

OpenRouter · OpenRouter · Original publication date 2026-08-21 · Site edit date 2026-09-20

Open original source

Ox Alpha

Compare Ox Alpha in Tabbit

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Read the full analysis

Overview · English

Ox Alpha Explained: From Stealth Preview to GLM-5.3-Flash

Ox Alpha was the anonymous name for Z.ai GLM-5.3-Flash. Here are the verified specs, access boundaries, preview timeline and safe testing decision.

Related reviews

Same Image, Same Prompt, Three Harnesses: Harness Effects on Ox AlphaLeMi compared the DeepSeek, OMP, and OpenCode frameworks using the same Ox Alpha, the same *Interstellar* Ranger RF-31D reference image, and the same prompt, suggesting that a harness may substantially affect results, but the post does not publish a quantitative score.Cline Test: Ox Alpha and Fable Both Fixed a Real Repository Bug, with About 3x Less OutputCline says Ox Alpha and Fable both correctly fixed one real bug in its repository; Ox Alpha used about three times fewer output tokens and repeated less reasoning. This is an efficiency signal worth retesting, not a general capability ranking.Independent LiveCodeBench v6: Ox Alpha's Raw Pass@1Under a single-turn code-generation protocol with no agent, tools, scaffold, or sampling and with temperature=0, the experimental repository reports that Ox Alpha scored 49/175, or Pass@1=28.0%, on LiveCodeBench release_v6, with lower pass rates as difficulty increased.OpenCode Official Observation: 26T Ox Alpha Tokens in Four DaysOpenCode reports that Ox Alpha processed 26T tokens in four days, showing heavy real-world use of the preview but saying nothing by itself about model quality, individual quotas, or availability.SVG structure smoke testA one-line SVG prompt for a dragon riding a bicycle is a quick way to check Ox Alpha's handling of structural relationships, physical plausibility, and executable SVG code.Custom-language long-task workflowGive Ox Alpha documentation for a custom language that cannot be in its training data, then implement the game and language feature in separate stages to test document reading, sustained coding, and regression verification.Stalled-agent triageWhen Ox Alpha appears stuck, first separate service-side errors from local scanning or MCP blocking, then use .ignore, snapshot: false, and temporary MCP removal to narrow the cause.Reference-driven frontend UI workflowWhen using Ox Alpha for frontend UI, providing actionable browser, animation, and aesthetic tools first, then having the model read reference sites, is usually more reusable than simply asking it to “make a beautiful page.”