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AI/ML API

The AI/ML API offers a comprehensive suite of advanced AI functionalities designed to meet a variety of needs, including text completion, image inference, speech-to-text, and text-to-speech capabilities. The API is engineered for seamless integration, exceptional performance, and secure API key management, ensuring a smooth and reliable user experience.

Key Features

  • Inference: Effortlessly evaluate and deploy models for a range of tasks including text generation, image analysis, and more. This feature allows users to leverage the power of advanced AI to draw meaningful inferences from various data types.
  • API Key Management: Securely generate, manage, and monitor API keys to ensure the safety and integrity of interactions with the API. This feature provides robust security measures to protect data and operations.
  • Broad Model Selection: Gain access to a diverse array of models tailored to various AI applications, allowing selection of the most appropriate model for specific tasks. This extensive model library supports a wide range of functionalities to address different AI challenges.

Start building with AI/ML API

To start using the AI/ML API, follow the detailed Quickstart guide which provides step-by-step instructions to set up the development environment and initiate the first API call. This guide is designed to help users quickly familiarize themselves with the API's capabilities and start leveraging its powerful features.

Authentication

API Key Management

To use the AI/ML API, an API key is required. This key is essential for authenticating requests to the API. API keys can be easily generated and managed through the account dashboard, ensuring secure access to the API services.

Sending Your First Request

After setting up the environment and obtaining an API key, proceed to send the first request. The API documentation provides detailed instructions and examples to help craft requests and understand responses, enabling full utilization of the AI/ML API's functionalities.

Authorization: Bearer YOUR_API_KEY

curl --location --globoff 'api.aimlapi.com/chat/completions' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
    "model": "gpt-3.5-turbo",
    "messages": [
        {
            "role": "user",
            "content": "What's API?"
        },
    ],
    "max_tokens": 512,
    "stream": false,
    
}'

👉 Read the documentation to find out more: https://docs.aimlapi.com/

AI/ML API AI technology page Hackathon projects

Discover innovative solutions crafted with AI/ML API AI technology page, developed by our community members during our engaging hackathons.

Arc Power

Arc Power

nano-agent treats cost as a live reasoning input. At every step, the agent decides: proceed, downgrade to a cheaper model, or skip — governed by a real USDC budget settled on Arc via Circle Gateway. Gemini 2.0 Flash handles fast inference, function calling, and Google Search grounding. Gemini 2.5 Pro verifies factual claims. Each tool call triggers HTTP 402 — the agent signs an EIP-3009 USDC authorization and retries with payment proof. Circle Gateway settles micropayments on Arc in under a second at sub-cent cost. A live dashboard shows spend, earned, step count, and model-tier decisions in real time. Benchmark: 416 steps · $0.240 spent · $0.276 earned · +15% margin · $0.0006/action average. A screen recording shows a $0.25 live run — budget bar draining, model tier switching, decision log printing go · downgrade · skip. Economy view breaks down cost: 77% data, 17% LLM, 4% verification. Two agent wallets earn independent revenue. TAM is $200B+ AI infrastructure. SAM is $15B agentic API economy — every autonomous agent calling external services is a potential payer. Revenue comes from per-step settlement margin, SDK licensing, and premium x402 tool endpoints with built-in payment rails. LangChain, AutoGen, and CrewAI treat cost as post-hoc billing. nano-agent makes it a real-time constraint on behavior. The Arc economics are the moat: the same 417 actions cost roughly $834 in Ethereum gas — 3,475 times more expensive — making per-step micropayments impossible anywhere else. On Arc mainnet, multi-agent economies — agents hiring agents, earning revenue — become self-sustaining. Every x402-compatible API becomes a paid tool layer. nano-agent is the budget runtime that keeps those economies solvent.