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Aayat AI – AI Model Price & Feature Lookup
x402
Aayat AI – AI Model Price & Feature Lookup is a paid API for AI agents from aayatai.com, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-02).
Search and filter AI language models by price, context window, features, and provider, returning ranked pricing data sourced from OpenRouter
Price / call$0.003
Success—
StatusUnknown
How this service works
Live prices and specs of 400+ AI models from every major provider (OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, Qwen...): USD per million input/output tokens, cached-input price, context length, max output, and features (tools, JSON, reasoning, vision). Filter by ?q=, provider, needs=tools,vision, minContext, maxInputPrice; sort by price, context or newest.
Output
Returns a JSON object containing a list of AI models with their IDs, names, providers, per-million-token input and output prices, context window sizes, supported features, input modalities, knowledge cutoff dates, and creation dates. Also includes total count of matching models before the limit and data source attribution with fetch timestamp.
Example use cases
Budget model selection for coding agent
“I need the cheapest model that supports tools and JSON output for my coding agent — show me the top 5 options sorted by price, maximum input price $2 per million tokens.”
Comparing large-context models from top providers
“Which models from Anthropic, OpenAI, and Google have the largest context windows? Sort by context length and show me the top 20.”
Finding a multimodal reasoning model
“I need a model that supports reasoning, vision, and audio input — what are my options sorted by price, and what do they cost per million tokens?”
Technical details
Endpoint
GEThttps://aayatai.com/ai/models?utm_source=zero.xyzWhen to prefer
Use this endpoint when an AI agent needs to programmatically select the best LLM for a task based on cost, capability, or context constraints — especially useful for coding agents or orchestration layers dynamically routing to the cheapest capable model. Prefer over manual research or static model lists when you need up-to-date pricing from OpenRouter across hundreds of models. Ideal for cost-optimization workflows or when building model selection logic into an agent pipeline.
Side effects
- No models match the filter combination (empty models array, count 0)
- Invalid feature name in 'needs' parameter returns error or empty results
- Invalid sort enum value causes request rejection
- minContext or maxInputPrice values outside allowed range cause validation error
- Payment failure via x402 if USDC balance is insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"count": 1,
"total": 458,
"models": [
{
"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
}
],
"source": "OpenRouter",
"fetchedAt": "2026-09-28T12:00:00.000Z"
}
}Tags
x402
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