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    Free OpenAI & Anthropic compatible LLM API

    A drop-in replacement for OpenAI and Anthropic APIs. Sign up, get $10 free credits, generate API keys, and use any LLM model with streaming, tool calling, and JSON mode.

    Multi-provider routing
    Backed by NVIDIA NIM & Groq with multi-key rotation for reliability.
    Streaming, tools, JSON mode
    Full OpenAI compatibility including SSE streaming, function calling, and structured output.
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    $10 free for Gmail users
    @gmail.com sign-ups get 10 credits (= $10). Other domains get 0.
    Quick start:
    POST /v1/chat/completions
    POST /v1/messages
    GET /v1/models
    GET /health
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    Why api.namansoni.in

    Everything you need from an LLM API

    A free, fast, OpenAI-compatible gateway to open-source LLMs on NVIDIA NIM and Groq.

    Streaming & tool calling

    SSE streaming, function calling, JSON mode, vision — all passed through to upstream. Use any OpenAI SDK unchanged.

    Multi-key rotation

    Multiple NVIDIA NIM & Groq API keys configured per server. Each request uses a random key; retries on 429.

    Pay-as-you-go credits

    1 credit = $1. Per-token billing identical to upstream pricing. $10 free for Gmail users.

    OpenAI + Anthropic schemas

    POST /v1/chat/completions for OpenAI clients, POST /v1/messages for Anthropic clients. Same models, both schemas.

    In-browser playground

    Test models before writing code. Adjust temperature, max tokens, system prompt, and copy as cURL.

    Full docs & snippets

    Copy-paste cURL, Python, and Node.js snippets. OpenAI and Anthropic SDK examples included.

    Code example

    Drop-in OpenAI replacement

    Change two lines in your existing code and you're done.

    from openai import OpenAI
    
    # Before:
    # client = OpenAI(api_key="sk-xxxx")
    
    # After:
    client = OpenAI(
        api_key="ns-xxxx",
        base_url="https://api.namansoni.in/v1",
    )
    
    response = client.chat.completions.create(
        model="llama-3.1-8b-instant",
        messages=[{"role": "user", "content": "Hello!"}],
        stream=True,
    )
    for chunk in response:
        print(chunk.choices[0].delta.content or "", end="")
    Read full docs
    Available models

    Powered by NVIDIA NIM & Groq

    Browse the full list of models with pricing, capabilities, and context windows. Each model is tested before listing.

    Browse models Try the playground
    FAQ

    Frequently asked questions

    Everything you need to know about the free LLM API.

    More questions

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