Free OxAlpha Chat

What is the free OxAlpha chat?

This page is a free, browser-based chat interface for OxAlpha, the stealth reasoning model that appeared on OpenRouter with no announcement and no named creator. OxAlpha is available at zero cost, and this chat passes your messages straight to it. There is no account to create, no email to confirm, and no trial clock counting down. You open the page, you type, and OxAlpha responds.

OxAlpha itself is unusual. Nobody outside its makers knows which lab trained OxAlpha or why it is free. What the community does know, from direct testing, is that OxAlpha reads a 1M-token context window, produces up to 131K output tokens per response, and reasons internally before it answers. On community-run evaluations, OxAlpha scores around 80% on an aggregate reasoning suite, ahead of GPT-5 at roughly 65%, Fable 5 at roughly 62%, and Grok 4 at roughly 58%. Those are directional community measurements, not official scores, but they explain why so many people want to try OxAlpha for themselves.

This site is an independent community resource. We are not affiliated with OpenRouter or with any AI lab, and we did not build OxAlpha. We built this chat because the fastest way to understand OxAlpha is to talk to it. If you want the deeper technical story, read how OxAlpha works; if you want the numbers, see the OxAlpha benchmarks.

How the OxAlpha chat works

The mechanics are simple. When you send a message, our server forwards it to OpenRouter, requests the model id stealth/ox-alpha, and streams the OxAlpha response back to your browser token by token. You see words appear as OxAlpha generates them, the same way you would in any modern AI chat. There is no hidden model swap: every reply on this page comes from OxAlpha and only from OxAlpha.

Streaming matters more with OxAlpha than with most models, because OxAlpha can produce very long answers: up to 131K output tokens in a single response. When you ask OxAlpha to write a full technical document or a complete module of code, the stream lets you start reading immediately instead of staring at a spinner. If an answer is heading in the wrong direction, you can stop it, refine your prompt, and send again, and OxAlpha picks up the conversation with the full history intact.

Thinking before answering

OxAlpha is a thinking-first model. Before it writes a single word of its visible answer, OxAlpha produces internal reasoning: it works through the problem, checks its own steps, and only then commits to a response. In practice this means a short pause before hard questions, followed by an answer that is noticeably more deliberate than what most free chats produce. If your question is trivial, OxAlpha replies almost instantly; if it is genuinely difficult, the wait is where the quality comes from.

The 1M-token context window

Because OxAlpha accepts up to one million tokens of context, you can paste enormous inputs into this chat: an entire codebase, a full contract, a long report, or hours of meeting transcripts. OxAlpha keeps track of the whole conversation as it grows, so multi-turn sessions stay coherent far longer than with typical free chatbots, which often forget the start of a long thread.

What to ask OxAlpha

OxAlpha is a general model, but community testing shows it is strongest in a few areas. If you want to see what separates OxAlpha from an ordinary chatbot, start with these.

Long-horizon coding

Paste a multi-file project and ask OxAlpha to find a bug, plan a refactor, or implement a feature end to end. OxAlpha holds the entire codebase in context, so it can reason about how a change in one file ripples through the others. Users report that OxAlpha stays on task across long agentic coding sessions where other models drift.

Complex, multi-step reasoning

Logic puzzles, math proofs, scheduling problems, strategy questions with many constraints: this is the category where OxAlpha posts its biggest benchmark lead. Give OxAlpha a problem you already know the answer to and watch how it gets there.

Structured output

Ask OxAlpha for strict JSON, a markdown table, or a filled template, and it follows the schema reliably. This makes OxAlpha useful for extracting structured data from messy text directly in the chat.

Multimodal questions

OxAlpha accepts text, images, and video as input. Support in this chat interface centers on text today, but the underlying OxAlpha model can describe screenshots, read diagrams, and analyze footage. The full list is on the OxAlpha capabilities page.

Writing, research, and analysis

Beyond code and logic, OxAlpha is a strong long-document worker. Paste a research paper and ask OxAlpha to summarize the methodology, challenge the conclusions, or compare it against a second paper in the same message. Hand OxAlpha a contract and ask what a specific clause obligates you to do. Give it a stack of customer feedback and request themes, counts, and representative quotes. Tasks that force other free chats to truncate their input are exactly where the OxAlpha context window pays off, because nothing has to be cut before OxAlpha reads it.

OxAlpha chat vs other free AI chats

Plenty of AI chats are free at the entry tier. The difference is what the free tier actually gives you. Most free chatbots serve a smaller or throttled model, cap your daily messages, and push you toward a subscription the moment you ask for anything heavy. OxAlpha is free at full strength: the same stealth/ox-alpha model, the same 1M-token context, the same thinking-first reasoning, whether you send one message or one hundred.

The other difference is capability. On community reasoning evaluations, OxAlpha at ~80% outscores the flagship paid models people compare it against, including GPT-5 and Fable 5. You are not choosing OxAlpha as the budget option; by the community numbers, you are choosing the strongest option that happens to cost nothing. For a detailed head-to-head, see OxAlpha vs GPT-5.

Context length is the other practical gap. Free tiers of the big commercial chats commonly limit you to a fraction of their paid context window, which means long documents get silently trimmed. The OxAlpha chat imposes no such split: the 1M-token window is the window, free. Combined with the 131K output ceiling, OxAlpha can take in more and give back more than any free chat we know of, which changes the kind of work you can do without paying anyone.

The honest caveat: OxAlpha is a stealth model. There is no SLA, no official documentation, and no promise it stays available forever. A free chat built on OxAlpha inherits that uncertainty. We think the trade is worth it while OxAlpha is here, and this page will say so plainly if the situation changes.

Privacy and prompting tips for OxAlpha

Privacy notes

No account means we never learn your name or email. Your messages are proxied through our server to OpenRouter so the chat can reach OxAlpha; we do not build profiles from them or sell them. Because OxAlpha’s operator is unknown, though, you should treat this like any third-party AI service: do not paste passwords, private keys, or sensitive personal data into the chat. That advice applies to OxAlpha exactly as it applies to every model whose infrastructure you do not control. More detail is on our about page.

Getting better answers from OxAlpha

A few habits make OxAlpha noticeably better. First, give it the full problem: OxAlpha has a huge context window, so include the whole file, the whole spec, the whole email thread, rather than a summary. Second, state your constraints explicitly, since OxAlpha reasons over what you write, not what you meant. Third, ask for the output format you want, because OxAlpha follows format instructions tightly. Finally, let hard questions take a moment; the pause is OxAlpha thinking, and interrupting it with a rephrased prompt just restarts the reasoning.

One more tip for complex work: break big goals into a first message that sets context and later messages that direct the work. Because OxAlpha retains the entire session, you can load a codebase or document set once, then interrogate it turn after turn without re-pasting anything. Treat the conversation as a workspace that OxAlpha maintains for you, and you will get far more out of the model than with one-shot prompts.

OxAlpha chat FAQ

Is the OxAlpha chat really free?

Yes. OxAlpha is served free on OpenRouter, and this site adds no charge on top. There is no message cap, no premium tier, and no hidden paywall. If OxAlpha ever stops being free upstream, we will say so here rather than quietly degrading the chat.

Do I need an account to talk to OxAlpha?

No. The OxAlpha chat on this page works without sign-up of any kind. You do not need an OpenRouter account either; our server handles the connection to OxAlpha for you.

Which model is actually answering me?

Every response comes from the model published on OpenRouter as stealth/ox-alpha, which the community calls OxAlpha. We never substitute a cheaper model, and we do not blend OxAlpha with anything else.

Why does OxAlpha pause before answering?

OxAlpha generates internal reasoning before its visible reply. That thinking phase is where OxAlpha earns its benchmark results, so a pause on a difficult question is normal and usually a good sign.

Can OxAlpha see images or video in this chat?

The OxAlpha model accepts text, images, and video. This chat interface currently focuses on text; multimodal input support is on our roadmap, and the underlying OxAlpha capability is already there.

Is my conversation with OxAlpha stored?

Your messages pass through our proxy to reach OxAlpha via OpenRouter. We do not attach them to an identity, because there is no identity to attach: the chat has no accounts. Avoid sharing secrets all the same, since no one outside its makers can audit what OxAlpha’s operator retains.

How does OxAlpha compare to GPT-5 or Fable 5?

On the community-run aggregate reasoning suite, OxAlpha measures around 80%, versus roughly 65% for GPT-5, 62% for Fable 5, and 58% for Grok 4. These are directional community numbers rather than official scores, but they are consistent across independent testers, and they match the day-to-day feel of using OxAlpha on hard problems in this chat.

Who made OxAlpha?

Nobody knows. OxAlpha surfaced as a stealth release with no lab attribution. The community speculates, tests, and benchmarks, but the origin of OxAlpha remains unconfirmed, and this independent site has no inside information.

Understand what you just talked to

The chat above is the fastest way to experience OxAlpha, but the interesting part is what happens under the hood: the thinking phase, the million-token context, and the architecture guesses the community has pieced together from OxAlpha’s behavior.

A reasonable way to spend your first session: ask OxAlpha one question from your actual work, something a search engine handles badly and a small chatbot fumbles. Then push harder. Paste the real document, the real code, the real data, and see whether the answer holds up. That test tells you more about OxAlpha in ten minutes than any benchmark table, and it costs you nothing to run. If the result impresses you, the same model is one line of configuration away in your own tools through OpenRouter, and the pages on this site cover the setup, the measured performance, and the open questions about where OxAlpha came from. If it disappoints you, tell us; this is a community project, and honest negative reports about OxAlpha are as welcome as the highlight reels.

Learn how OxAlpha works