30+ mainstream models readyView models →

One API
to access the world's top AI models

Unified model interface, smart routing and transparent billing. No repeated integrations — ship every AI app faster and run it steadier.

Trusted by 2,000+ developers

One endpoint for mainstream models from 14 providers

OpenAIClaudeGeminiDeepSeekxAIQwenMoonshotVolcengineHunyuanWenxinQingyanCohereSunoXinference
Available models
30+
Service availabilityLive
99.99%
Added gateway latency
< 50ms
Technical support
7×24
Core capabilities

From your first line of code to stable operations

An AI infrastructure layer for developers that solves model access, reliability, cost and security in one place.

Smart routing & failoverAuto failover
● Shanghai · Edge 0112ms
● Tokyo · Edge 0326ms · active
● Los Angeles · Edge 07529 · tripped

→ Upstream issue · auto-switched Edge 07 → Edge 03

The problem first

Why not call each provider directly?

Direct integration works — until you're maintaining a third SDK, a fifth key, and yet another bill that doesn't reconcile. The cost of scattered integrations isn't on day one; it's every day after.

BEFORE

One integration per provider

WITH WANDAPI

One entry through WandAPI

Access

A separate SDK, auth scheme and response format per vendor — upgrades chased one by one
One endpoint natively speaking the OpenAI and Anthropic protocols — switching models is a one-string change

Keys

Keys scattered across repos and teammates; nobody knows who uses which
One key for every model, with quotas, rate limits and IP allowlists managed centrally

Failover

Upstream turbulence means hand-written retries — and 3am manual switchovers
Routes picked in real time by latency and health; upstream failures fail over in milliseconds

Billing

Month-end bills exported from each console and stitched together; cost attribution is guesswork
Every call on one bill, with per-request tokens and cost visible live
Workflow

Up and running in four steps

From sign-up to production monitoring, WandAPI onboarding takes four steps.

About 5 minutes
  1. wandapi.com/register
    [email protected]Sign up✓ Trial credit claimed
    1

    Sign up

    Create an account, claim your trial credit and generate your first API key.

  2. .env

    BASE_URL=https://api.wandapi.com

    API_KEY=sk-wand-••••3f9a

    2

    Configure

    Drop the base URL and API key into your existing SDK or tool — nothing else changes.

  3. POST /v1/messages
    model: "claude-fable-5"
    200 OK0.38s
    3

    Call

    Natively compatible with the OpenAI and Anthropic protocols — reach Claude, Gemini and other leading models directly.

  4. wandapi.com/console
    Success rate99.99%
    4

    Monitor

    Watch usage, cost and latency live in the console — anomalies stand out at a glance.

What developers say

Once they switch, they stay

Pointing Claude Code's base URL here took a minute. The night one upstream got rate-limited, I didn't even notice — the console showed it had failed over twice.
FAQ

Frequently asked questions

The things people ask before deciding.

A unified LLM API gateway, an OpenRouter-style alternative: your app talks to WandAPI's single endpoint, and we route each request to the best channel across Anthropic, OpenAI, Gemini and more — handling failover, metering and billing. To your code it's an OpenAI- and Anthropic-compatible endpoint, so Claude Code, Codex and any OpenAI SDK connect by changing one base URL.

Direct integration spreads routing logic, credentials and observability across every client. Through WandAPI they converge into one control plane: switch models without code changes, fail over automatically, and read one bill. You write product, not infrastructure.

Pay as you go — top up and use, no monthly fee, no minimum. Prices follow each model’s per-token price list with per-request line items; the price on the models page is what you actually pay, discounts shown explicitly.

Data masking is built in: when enabled, requests are scanned before forwarding and sensitive content — API keys, tokens, email addresses — is automatically redacted. The rule set (based on gitleaks and other open-source rules) updates itself on a schedule, and you can toggle it in your personal settings. Beyond that, requests are relayed over TLS end to end, we never train models on your data, and logs keep only the token counts and timing metadata needed for metering.

Every upstream key has a circuit breaker and sliding-window health metrics with request-level failover; the platform also probes major models on a schedule, and their latency and availability are public to all users on the Model Health page.

Didn’t find your answer? Sign up for free trial credit and integrate in five minutes — or browse the models page for prices and live health first.

Start building your next AI product with one API

Simpler AI infrastructure, faster product iteration.