# AI Model Price API (3,974 LLM models) (`fruitful_quintessence/ai-model-price-api`) Actor

LLM API pricing for 3,974 models / 749 providers. Search by keyword, provider, price. Updated 6h from OpenRouter + LiteLLM. Returns per-1M-token input/output prices, context length, modalities. For AI agents & cost tools.

- **URL**: https://apify.com/fruitful\_quintessence/ai-model-price-api.md
- **Developed by:** [atushi ino](https://apify.com/fruitful_quintessence) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## AI Model Price API (LLM Pricing Database)

**4000+ LLM モデルのAPI価格データベース**。LiteLLM + OpenRouter の公式データを統合。

### 機能

- モデル名・プロバイダで価格検索
- Input/Output/Cached トークン単価 ($/1M tokens)
- Context Length 対応

### 入力

| フィールド | 型 | 必須 | 説明 |
|---|---|---|---|
| keyword | string | いいえ | モデル名検索 (例: `gpt-4`, `claude`, `llama`) |
| provider | string | いいえ | プロバイダフィルタ (例: `openai`, `anthropic`) |
| limit | integer | いいえ | 最大件数 (default 50) |

### 出力

- `modelId` / `displayName` — モデルID
- `provider` — プロバイダ (openai, anthropic, google, ...)
- `inputPrice` / `outputPrice` — $/1M tokens
- `cachedInputPrice` — キャッシュ入力価格
- `contextLength` — 最大コンテキスト長
- `lastUpdated` — 更新日時

### 競合優位

- pricepertoken.com: 626モデル → **本Actor 3,974モデル (6.3倍)**
- llmpricecheck.com: GPT-4o が 2023-10 のまま → **本Actor は毎回最新取得**
- LiteLLM (3,561) + OpenRouter (+413) の2ソース統合

# Actor input Schema

## `keyword` (type: `string`):

Search keyword in model name / ID (e.g. 'gpt-4', 'claude', 'sonnet'). Leave empty to list all.

## `provider` (type: `string`):

Filter by provider name (e.g. 'openai', 'anthropic'). Optional.

## `limit` (type: `integer`):

Maximum number of models to return (1-10000).

## Actor input object example

```json
{
  "limit": 100
}
```

# Actor output Schema

## `modelId` (type: `string`):

Model ID (e.g. openai/gpt-4o)

## `displayName` (type: `string`):

Human-readable model name

## `provider` (type: `string`):

Provider name (e.g. openai)

## `contextLength` (type: `string`):

Context window in tokens (empty if unknown)

## `inputPrice` (type: `string`):

Input cost per 1M tokens in USD (empty if unknown)

## `outputPrice` (type: `string`):

Output cost per 1M tokens in USD (empty if unknown)

## `cachedInputPrice` (type: `string`):

Cached input cost per 1M tokens in USD (empty if unknown)

## `source` (type: `string`):

Data source: openrouter or litellm

## `lastUpdated` (type: `string`):

ISO 8601 UTC timestamp of last data update

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("fruitful_quintessence/ai-model-price-api").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("fruitful_quintessence/ai-model-price-api").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call fruitful_quintessence/ai-model-price-api --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fruitful_quintessence/ai-model-price-api"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/6EvRs5kF1mbelC03M/builds/VtTl8Qb4hLZHTwUdE/openapi.json