OnAPI vs PSEUDO.AI

OnAPI is a unified API gateway that lets developers call GPT, Claude, Gemini, Sora, Veo, and Google's Nano Banana image model through a single key. Swap your SDK base URL to OnAPI's endpoint, plug in an OnAPI key, and keep the rest of your integration unchanged.

The gateway speaks OpenAI-compatible and Anthropic-compatible protocols, so chat completions, Anthropic messages, streaming, function calling, and long-context requests work without a rewrite. OnAPI says new upstream models typically appear within 24 hours of release.

Two routing channels share the same account. The economy channel bills at a 1:1 rate multiplier for everyday volume. The official channel routes through paid keys tied directly to provider accounts at a 1:7.5 multiplier when you need a straighter path to upstream APIs.

OnAPI is aimed at builders shipping AI products, especially where direct provider billing is inconvenient. Top-ups run through Alipay, WeChat, USDT, and USDC. Account balance does not expire, and the site states there is no minimum spend.

The service runs on the open-source New API project (based on One API), which handles model aggregation and cross-format conversion between provider APIs.

PSEUDO.AI turns source code into human-readable pseudocode in your browser. You enter a prompt or code snippet, pick a language, and the app returns plain-language steps that read like structured pseudocode rather than raw syntax. It runs on the web at pseudoai.vercel.app with no install, and targets teams who need to explain implementation details to people who do not read code daily.

Most code explainers summarize what a snippet does in prose. PSEUDO.AI keeps the output closer to pseudocode structure, which makes handoffs to designers, product owners, or junior developers easier to scan. The trade-off is focus: it is built for pseudocode conversion, not debugging, testing, or repo-wide documentation. That narrow scope is the point when the goal is shared comprehension, not a full IDE workflow.

Software developers use it to translate tricky logic before code reviews or stakeholder meetings. Computer science students and instructors lean on it when a textbook example needs a readable walkthrough. Product managers and mentors who sit in technical discussions but do not write production code get a format they can follow without parsing braces and semicolons.