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AI Infrastructure

Multi-LLM RouterOne API key, every AI model

The Helix Multi-LLM Router API gives you OpenAI-compatible access to GPT-4, Claude, Gemini, Llama, Mistral, Qwen, and 50+ other models through one endpoint and one API key. Switch models with a single string change, compare outputs side-by-side, or set fallback chains for high availability.

  • Free tier with 100 requests/month
  • Fast, cached responses
  • 99.9% uptime target
  • Standard REST + JSON
Interactive Demo
Multi-LLM Chat (13 models)

Ask anything to start chatting… (sample responses)

What is the Multi-LLM Router API?

The Helix Multi-LLM Router API gives you OpenAI-compatible access to GPT-4, Claude, Gemini, Llama, Mistral, Qwen, and 50+ other models through one endpoint and one API key. Switch models with a single string change, compare outputs side-by-side, or set fallback chains for high availability.

How it works

  1. 1POST messages to /chat in OpenAI format — same shape you already use.
  2. 2Set `model` to any of 50+ supported names (gpt-4o, claude-3.5-sonnet, gemini-1.5-pro, llama-3.1-405b, etc.) or `auto` for cheapest/fastest routing.
  3. 3POST to /compare to send the same prompt to 3+ models and get a side-by-side response.
  4. 4Set `fallback_models` array — if the primary fails or times out, we try the next one transparently.
  5. 5Streaming, function calling, JSON mode, and vision are all supported via the same endpoint.

Endpoints

3 REST endpoints, all returning consistent JSON.

POST
/chat

Send chat completion request

GET
/models

List available models

POST
/compare

Same prompt to multiple models

Code in 5 languages

Copy and paste into your project. Replace YOUR_API_KEY with your RapidAPI key.

// Multi-LLM Router API
const response = await fetch(
  "https://multi-llm-router-by-helix-api.p.rapidapi.com/chat",
  {
    method: "POST",
    headers: {
      "X-RapidAPI-Key": "YOUR_API_KEY",
      "X-RapidAPI-Host": "multi-llm-router-by-helix-api.p.rapidapi.com",
      "Content-Type": "application/json"
    },
    body: JSON.stringify({ "query": "your input" })
  }
);

const data = await response.json();
console.log(data);

What developers build with this API

Real use cases from production deployments.

1

Vendor Lock-in Insurance

Build your product against one stable API. Switch from GPT-4 to Claude overnight if pricing changes or quality regresses. No code rewrite.

2

Cost Optimization via Smart Routing

Route easy queries to GPT-4o-mini ($0.15/M tokens), reserve GPT-4o ($2.50/M) for hard problems. Auto-routing typically cuts costs 60-80% with no quality loss.

3

A/B Testing Models in Production

Send 50% of traffic to Claude, 50% to GPT-4. Compare user satisfaction, task completion, and costs in your own analytics.

4

Failover for High-Availability AI

OpenAI outages happen. Set `fallback_models: ['claude-3.5-sonnet', 'gemini-1.5-pro']` and your product never goes down.

5

Side-by-Side Comparison UIs

Build the next ChatGPT/Claude/Gemini comparison tool. /compare returns synchronized responses from N models in one request.

Pricing

All tiers include this API. No credit card for free tier.

BASIC

Free

  • 100 reqs/month
  • Hard limit
  • ✓ All endpoints
Most Popular

PRO

$9.99/mo

  • 10,000/month
  • +$0.005 each
  • ✓ All endpoints

ULTRA

$29.99/mo

  • 100,000/month
  • +$0.002 each
  • ✓ All endpoints

MEGA

$99.99/mo

  • 1,000,000/month
  • +$0.001 each
  • ✓ All endpoints

View all 20 APIs included →

Frequently asked questions

Real answers to questions developers ask before integrating.

Is it really OpenAI-compatible?
Yes — same /chat/completions shape, same message format, same streaming protocol. Replace `https://api.openai.com/v1` with our base URL and most code just works.
What models are supported?
GPT-4o, GPT-4o-mini, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro/Flash, Llama 3.1 (8B/70B/405B), Mistral Large/Small, Qwen 2, Phi-3, and 40+ more. Full list at /models.
How does pricing work?
You pay our markup on the underlying model cost. Mostly within 5-10% of going direct to the model vendor — and you get unified billing across all providers.
Can I use function calling?
Yes — full OpenAI function calling spec is supported across models that natively support it (GPT-4o, Claude, Gemini).
What about streaming?
SSE streaming works the same way as OpenAI. Set `stream: true` and read tokens as they arrive.
Do you log my prompts?
No — we never log prompts or responses (only metadata for billing). Inputs are forwarded to the model vendor and discarded.

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