Aayat AI – AI Model Picker

x402

Aayat AI – AI Model Picker is a paid API for AI agents from aayatai.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-02).

Recommends and ranks AI models from OpenRouter based on task description, required features, token budget, and quality tier

Price / call$0.01

Seller volume →—

Success—

StatusUnknown

How this service works

Cheapest AI model that can do your job. Describe the task (or list needed features: tools, json, reasoning, vision...), expected input/output tokens and a quality level (budget/balanced/best); get the cheapest suitable models across all major providers with estimated USD cost per call and per 1,000 calls, from live prices. POST {task, inputTokens, outputTokens}.

Output

Returns a ranked list of AI models (up to 50) from OpenRouter, each with name, provider, input/output pricing per million tokens, context length, supported features, estimated cost per call, and a top recommended model with a full explanation of how requirements were derived and matched.

Example use cases

Cheapest vision model for image pipelines

“I'm building an image analysis pipeline. What's the most budget-friendly model that supports vision and JSON output, assuming 2000 input tokens and 300 output tokens per call? Show me the top 3 options.”

Best reasoning model for complex coding agent

“My coding agent needs strong reasoning and tool-calling support. It sends about 5000 input tokens and gets back 1000 output tokens per call. Find me the best quality model from OpenRouter that fits, and tell me the estimated cost per call.”

Cheapest OpenAI or Anthropic model with 100k context

“I need a model from either OpenAI or Anthropic with at least 100000 token context window, that supports function calling. My typical call is 4000 input tokens and 800 output tokens. What's the cheapest option?”

Technical details

Endpoint

POSThttps://aayatai.com/ai/models/pick?utm_source=zero.xyz

When to prefer

Use this endpoint when an AI agent needs to programmatically select the optimal LLM for a subtask — especially when balancing cost, capability (vision, tools, reasoning, JSON), and context window requirements. Prefer over manually hardcoding a model name, or when the best model may change over time. Ideal for agentic coding assistants, multi-model routing systems, or cost-optimization layers. No API key or account required — pay per call with USDC on Base or Solana.

Side effects

Invalid or unsupported feature name in 'needs' field returns an error
Overly restrictive filters (provider + features + context) may return zero candidates
Payment failure via x402 if insufficient USDC balance on Base or Solana
Task description too vague may result in poor AI-inferred feature matching
minContext value exceeding available model limits returns empty candidate list

Input

Schema · Request body

Field	Type	Description
task	string	What the model must do, in plain words. An AI reads it to work out the needed features and quality.
limit	integer	How many ranked models to return.
needs	string	Comma list of required features (added to any the task implies): tools, json, reasoning, vision, audio, files, web-search.
quality	string	budget, balanced or best. If a task is given, the AI's judgement is used unless you set this to something other than balanced.
providers	string	Only these providers, comma separated (e.g. anthropic,openai).
minContext	integer	Minimum context window (default: input + output tokens).
includeFree	boolean	Include free, rate-limited variants.
inputTokens	integer	Typical input (prompt) tokens per call.
outputTokens	integer	Typical output tokens per call.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "method": "Hard filters (features, context, output limit, provider), a price-based quality floor, then cheapest estimated cost per call.",
    "source": "OpenRouter",
    "fetchedAt": "2026-09-28T12:00:00.000Z",
    "candidates": [
      {
        "id": "google/gemini-2.5-flash",
        "free": false,
        "name": "Google: Gemini 2.5 Flash",
        "created": "2025-06-17",
        "features": [
          "tools",
          "json",
          "reasoning",
          "vision",
          "audio",
          "files"
        ],
        "provider": "google",
        "inputPerMTok": 0.3,
        "contextLength": 1048576,
        "outputPerMTok": 2.5,
        "perRequestUsd": 0,
        "inputModalities": [
          "text",
          "image",
          "file",
          "audio"
        ],
        "knowledgeCutoff": null,
        "maxOutputTokens": 65535,
        "cachedInputPerMTok": 0.075,
        "estimatedCostPerCallUsd": 0.0019
      }
    ],
    "considered": 458,
    "recommended": {
      "id": "google/gemini-2.5-flash",
      "free": false,
      "name": "Google: Gemini 2.5 Flash",
      "created": "2025-06-17",
      "features": [
        "tools",
        "json",
        "reasoning",
        "vision",
        "audio",
        "files"
      ],
      "provider": "google",
      "inputPerMTok": 0.3,
      "contextLength": 1048576,
      "outputPerMTok": 2.5,
      "perRequestUsd": 0,
      "inputModalities": [
        "text",
        "image",
        "file",
        "audio"
      ],
      "knowledgeCutoff": null,
      "maxOutputTokens": 65535,
      "cachedInputPerMTok": 0.075,
      "estimatedCostPerCallUsd": 0.0019,
      "estimatedCostPer1000CallsUsd": 1.9
    },
    "requirements": {
      "needs": [
        "json",
        "vision"
      ],
      "reason": "Reads images and returns structured data.",
      "quality": "balanced",
      "minContext": 3400,
      "inputTokens": 3000,
      "outputTokens": 400
    }
  }
}

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