# Ai Model Pricing (`pink_fence/ai-model-pricing`) Actor

Scrape live AI model pricing from OpenAI, Anthropic, Google Gemini and Mistral in one run. Input and output price per 1M tokens, context window size and more. Perfect for cost tracking and n8n workflows.

- **URL**: https://apify.com/pink\_fence/ai-model-pricing.md
- **Developed by:** [Moritz Knopp](https://apify.com/pink_fence) (community)
- **Categories:** AI, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.00005 / actor start

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## 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 Pricing Scraper

This Apify Actor scrapes **live AI model pricing** from the official websites of OpenAI, Anthropic, Google Gemini, and Mistral — all in a single run. It returns structured data including input and output price per 1 million tokens, context window size, and a timestamp, so you always have up-to-date pricing without manually checking four different websites.

***

### Input Parameters

| Field       | Type            | Required | Default                                          | Description                                                                 |
|-------------|-----------------|----------|--------------------------------------------------|-----------------------------------------------------------------------------|
| `providers` | Array of strings | No       | `["openai", "anthropic", "gemini", "mistral"]`  | Which providers to scrape. Omit this field to scrape all four providers.    |

**Accepted values for `providers`:** `"openai"`, `"anthropic"`, `"gemini"`, `"mistral"`

***

### Output Fields

Each item pushed to the dataset represents one AI model and contains:

| Field                     | Type    | Description                                                        |
|---------------------------|---------|--------------------------------------------------------------------|
| `provider`                | String  | Provider name, e.g. `"OpenAI"`                                     |
| `modelName`               | String  | Human-readable model name, e.g. `"gpt-4o"`                        |
| `modelId`                 | String  | API identifier of the model, e.g. `"gpt-4o-2024-08"`              |
| `inputPricePer1MTokens`   | Number  | Cost in USD per 1 million input tokens, e.g. `5.00`               |
| `outputPricePer1MTokens`  | Number  | Cost in USD per 1 million output tokens, e.g. `15.00`             |
| `contextWindow`           | String  | Maximum context window size, e.g. `"128k"`                        |
| `lastScraped`             | String  | ISO 8601 timestamp of when the data was collected                  |

***

### Example Input

```json
{
  "providers": ["openai", "anthropic"]
}
```

To scrape all four providers, send an empty input or omit the field entirely:

```json
{}
```

***

### Example Output

```json
[
  {
    "provider": "OpenAI",
    "modelName": "gpt-4o",
    "modelId": "gpt-4o-2024-08",
    "inputPricePer1MTokens": 5.00,
    "outputPricePer1MTokens": 15.00,
    "contextWindow": "128k",
    "lastScraped": "2026-05-10T12:00:00.000Z"
  },
  {
    "provider": "Anthropic",
    "modelName": "claude-3-5-sonnet-20241022",
    "modelId": "claude-3-5-sonnet-20241022",
    "inputPricePer1MTokens": 3.00,
    "outputPricePer1MTokens": 15.00,
    "contextWindow": "200k",
    "lastScraped": "2026-05-10T12:01:34.000Z"
  },
  {
    "provider": "Google Gemini",
    "modelName": "gemini-1.5-pro",
    "modelId": "gemini-1.5-pro",
    "inputPricePer1MTokens": 3.50,
    "outputPricePer1MTokens": 10.50,
    "contextWindow": "1M",
    "lastScraped": "2026-05-10T12:02:58.000Z"
  }
]
```

***

### Use Case Ideas

- **Cost optimisation** — Compare prices across providers and programmatically pick the cheapest model that meets your quality threshold.
- **Price alerts** — Schedule this Actor to run daily and trigger a notification (via [Make](https://make.com), [n8n](https://n8n.io), or [Zapier](https://zapier.com)) whenever a price changes.
- **AI budget tracking** — Feed pricing data into a spreadsheet or dashboard to forecast monthly LLM spend based on token usage.
- **Competitive analysis** — Track how providers adjust prices over time and spot market trends.
- **Automation integrations** — Connect the dataset to n8n, Make, or Zapier to automatically update internal pricing tables, Notion databases, or Slack channels whenever new data is scraped.

***

### Running Locally

```bash
## Install dependencies
npm install

## Run the Actor
npm start
```

Set your `APIFY_TOKEN` environment variable if you want data pushed to the Apify cloud dataset. Without it the Actor writes data locally to `./storage/datasets/default/`.

***

### Tech Stack

- [Node.js](https://nodejs.org/) 18+
- [Apify SDK](https://docs.apify.com/sdk/js/) — Actor lifecycle, input/output handling
- [Crawlee](https://crawlee.dev/) — `PlaywrightCrawler` for JS-rendered pages
- [playwright-extra](https://github.com/berstend/puppeteer-extra/tree/master/packages/playwright-extra) + [stealth plugin](https://github.com/berstend/puppeteer-extra/tree/master/packages/puppeteer-extra-plugin-stealth) — avoid bot detection

# Actor input Schema

## `providers` (type: `array`):

List of providers to scrape. Options: openai, anthropic, gemini, mistral. Leave empty to scrape all.

## Actor input object example

```json
{
  "providers": [
    "openai",
    "anthropic",
    "gemini",
    "mistral"
  ]
}
```

# 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("pink_fence/ai-model-pricing").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("pink_fence/ai-model-pricing").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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 pink_fence/ai-model-pricing --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=pink_fence/ai-model-pricing",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UaGmr6m5nRvsiXryj/builds/XPtuy2IMfgEdYZSL4/openapi.json
