- Ox Alpha model: A stealth reasoning model focused on coding and sustained agentic work
- Access method: Use the OpenRouter API with the model slug
stealth/ox-alpha - Context window: Supports a reported 1M-token context for long-running projects
- Pricing status: OpenRouter currently lists input and output pricing as $0
- Best fit: Long-horizon software engineering, production workflows, and visual-context tasks
Ox Alpha Model Overview
The Ox Alpha model is a third-party stealth model available through OpenRouter. It is positioned for coding, extended agentic work, complex reasoning, and production workloads that may combine text with visual context. The provider remains anonymous during the preview, while OpenRouter acts as the routing platform rather than the model’s developer or owner.
The model was listed as released on August 20, 2026. Its current profile identifies a 1M-token context window, text output, and support for text, image, and video input. That combination makes Ox Alpha especially relevant for developers working with large repositories, lengthy technical specifications, visual references, or multi-step automation tasks.
Coding Focus
- Designed for software engineering
- Useful for multi-file code tasks
- Supports test-and-iterate workflows
Agentic Work
- Built for sustained task execution
- Suitable for long-horizon planning
- Works with tool-enabled applications
Visual Context
- Accepts image and video input
- Helps connect code with visual references
- Returns text responses
| Profile Item | Current Listing |
|---|---|
| Model name | Ox Alpha |
| Model slug | stealth/ox-alpha |
| Provider type | Anonymous third-party stealth provider |
| Release date | August 20, 2026 |
| Context window | 1M tokens |
| Listed pricing | $0 input / $0 output |
| Available through | OpenRouter |
Ox Alpha is operated by an anonymous third-party provider during its preview. Review the applicable Stealth Model Terms before sending sensitive or regulated information.
For the latest availability, endpoint details, and provider disclosures, consult the Ox Alpha API pricing and provider page on OpenRouter.
Best Use Cases and Workflow Fit
Ox Alpha is most compelling when a task requires more than a short answer. Its stated focus on sustained agentic work suggests a good fit for workflows that involve planning, editing, testing, and revising over several stages.
Common applications include:
- Repository analysis: Review a large codebase before proposing changes.
- Multi-file implementation: Plan a change, update related files, and explain the impact.
- Debugging loops: Inspect an error, suggest a fix, evaluate test output, and revise.
- Technical research: Keep specifications, logs, and implementation notes in one context.
- Visual-assisted development: Combine screenshots, diagrams, or video references with coding instructions.
- Production automation: Connect the model to an application that needs structured requests and responses.
The model’s large context window can reduce the need to repeatedly summarize long project materials. However, a large context limit does not automatically guarantee that every prompt will produce the best result. Clear objectives, bounded tool permissions, and explicit success criteria remain important.
| Workflow | Why Ox Alpha May Fit | Recommended Prompt Detail |
|---|---|---|
| Code review | Large context can hold extensive project material | State the review scope and severity levels |
| Bug fixing | Supports iterative reasoning and test feedback | Include logs, expected behavior, and constraints |
| Agent automation | Designed for sustained agentic work | Define tools, stop conditions, and approval points |
| Visual analysis | Accepts image and video input | Explain what visual details matter to the task |
| Documentation | Handles long technical references | Specify audience, format, and terminology |
Long Context
Keep related files, requirements, and logs together when the task benefits from broader project awareness.
Structured Tasks
Break complex work into goals, constraints, validation steps, and final deliverables.
Tool Control
Give agents only the tools and permissions needed for the current operation.
Visual Inputs
Use screenshots, diagrams, or video when they provide information that text alone cannot capture.
Start with the desired outcome, then define the available files, tools, constraints, and verification method. This gives a long-running agent a clearer operating boundary.
Pricing, Providers, and Performance
OpenRouter currently lists Ox Alpha as a free model, showing $0 per million input tokens and $0 per million output tokens for the available provider. Pricing can change, and the page notes that displayed customer costs may be affected by caching, discounts, or provider pricing updates.
The current provider snapshot reports a P50 latency of 5.30 seconds, throughput of 23 tokens per second, and provider uptime of 100.00% in the displayed measurement. OpenRouter also reports 99.99% uptime and 99.51% availability over the previous three days on the captured page. These values are time-sensitive operational metrics rather than permanent guarantees.
| Metric | Current Reported Value | How to Read It |
|---|---|---|
| Input price | $0 per million tokens | Listed provider price at capture time |
| Output price | $0 per million tokens | Listed provider price at capture time |
| P50 latency | 5.30 seconds | Typical round-trip latency in the provider snapshot |
| Throughput | 23 tokens per second | Reported generation speed in the provider snapshot |
| Provider uptime | 100.00% | Displayed provider measurement |
| Three-day availability | 99.51% | Recent service availability measurement |
The provider section states that OpenRouter forwards requests directly to one provider, so there are no routing decisions between multiple listed providers in the current snapshot. OpenRouter may still provide recovery or routing options when configured endpoints allow it, so production teams should verify their own request filters and fallback settings.
A second performance consideration is tool reliability. The captured page reports an average tool-call error rate of 2.27% and an average cache hit rate of 81.72% for the displayed provider data. These figures can help frame testing priorities, but they should not replace application-level monitoring.
Treat latency, throughput, availability, and tool-call rates as snapshots from August 2026. Run your own representative workload before selecting Ox Alpha for a critical production path.
| Deployment Concern | Practical Response |
|---|---|
| Variable latency | Stream responses and show progress in the interface |
| Tool-call failures | Add validation, retries, and clear failure states |
| Provider changes | Monitor model behavior and endpoint status |
| Long prompts | Track token usage and keep context relevant |
| Preview uncertainty | Maintain a fallback model for important workflows |
Step-by-Step API Setup
OpenRouter describes its API as OpenAI-compatible, allowing many existing SDK-based applications to switch models by changing the base URL, credentials, and model identifier. The following setup path focuses on a small, testable integration rather than immediately deploying an autonomous workflow.
Create an API Key
Create an API key in the OpenRouter dashboard. Store it outside your source code and expose it to your application through an environment variable such as OPENROUTER_API_KEY.
Set the Model Slug
Use stealth/ox-alpha as the model identifier. Confirm that the account, endpoint, and current provider availability permit access before running a larger workload.
Send a Small Request
Begin with a short coding or reasoning prompt. Check the response structure, error handling, latency, and token usage before introducing tools or large context inputs.
Enable Streaming
Add "stream": true when your interface benefits from incremental output. Streaming can make longer responses feel more responsive while the model generates them.
Add Validation and Monitoring
Validate model output, log request outcomes, measure tool-call failures, and define a fallback path for errors or service changes.
A minimal request should remain easy to inspect. The model page presents OpenRouter-specific headers such as HTTP-Referer and X-Title as optional ranking-related fields. They are not required for the core request shown in the quick-start material.
| Parameter | Type | Default | Purpose |
|---|---|---|---|
max_tokens | Integer | Not specified | Sets the upper limit for generated output |
temperature | Float | 1 | Influences response variety |
top_p | Float | 0.95 | Limits selection to a probability mass |
tools | Array | Not specified | Defines callable tools |
tool_choice | String or object | Not specified | Controls tool selection |
top_k | Integer | 0 | Narrows token choices at each step |
response_format | Map | Not specified | Requests a structured output format |
Use a non-sensitive prompt and a small response limit first. Confirm authentication, model selection, streaming behavior, and error handling before adding private project data.
Production Checklist and Practical Limits
Ox Alpha can be tested as a general-purpose coding and agentic model, but production readiness depends on the surrounding application. The model page identifies the provider as third-party and states that prompts and completions are retained by the provider and are not used for training. Other usage is governed by the Stealth Model Terms, so teams should review those terms against their own privacy, compliance, and retention requirements.
Use this checklist before moving from experimentation to a persistent workflow:
Production Readiness Checklist:
- Review the Stealth Model Terms and provider data-retention statement
- Remove secrets, credentials, and unnecessary personal data from prompts
- Test coding tasks with representative repositories and failure cases
- Add streaming, timeout handling, retries, and fallback behavior
- Monitor latency, availability, tool-call errors, and output quality
A strong operating pattern is to separate planning from execution. Ask the model to identify affected files and risks before allowing changes. For tool-enabled agents, require confirmation before destructive actions such as deleting files, changing deployment settings, or modifying production data.
Additional safeguards include:
- Use read-only tools during the first evaluation phase.
- Require machine-checkable output for automated actions.
- Keep tests and linters in the execution loop.
- Cap the number of retries for failing tool calls.
- Record the prompt version and model slug with each important run.
- Recheck pricing and availability before scaling usage.
Do not assume that a zero listed price means zero operational risk. Privacy terms, provider retention, application logs, and tool permissions still require careful review.
Ox Alpha Model FAQ
Q: What is the Ox Alpha model?
Ox Alpha is a stealth reasoning model designed for coding, sustained agentic work, complex reasoning, and production workloads. It is operated by an anonymous third-party provider and accessed through OpenRouter.
Q: Is Ox Alpha free to use?
OpenRouter currently lists Ox Alpha at $0 for input and output tokens through the displayed provider. Pricing and access conditions can change, so check the live model page before relying on the current listing.
Q: What inputs does Ox Alpha support?
The current listing describes support for text, images, and video as input, with text returned as output. Use visual inputs when they add information that is difficult to express in text.
Q: How do I call Ox Alpha through an API?
Create an OpenRouter API key, set the model to stealth/ox-alpha, and send a request through the OpenRouter-compatible API. Streaming can be enabled with stream set to true.
Evaluate Ox Alpha with a focused coding benchmark, a tool-use test, and a multimodal task. Compare quality and reliability against your existing model before expanding the workflow.