# AI Model Catalog & Pricing Finder (`fetchfinch/ai-model-catalog`) Actor

Search and export current AI model metadata with provider filters, capability flags, context limits, modalities, and normalized token pricing.

- **URL**: https://apify.com/fetchfinch/ai-model-catalog.md
- **Developed by:** [Fetch Finch](https://apify.com/fetchfinch) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.10 / 1,000 model records

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/actors/running/actors-in-store.md#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 Catalog

Search and export a current catalog of AI models as an Apify dataset. Each run fetches the latest available metadata, applies your filters, and returns one normalized record per model.

No API key is required. The catalog is refreshed at run time, so pricing, availability, and capabilities should be treated as changeable information and verified with the provider before production use.

### What you get

Every dataset item can include:

- Model ID, name, provider, family, and description
- Context window and maximum completion token limits
- Supported input and output modalities
- Token pricing normalized to USD per million tokens
- Tool calling, reasoning, structured output, vision, audio, and video flags
- Supported parameters, model weights, benchmarks, release dates, and expiration dates when available
- A retrieval timestamp and the catalog URL used for that run

The run also saves a `RUN_SUMMARY` record in the default key-value store with the number of models received, matched, and written, together with the filters used.

### Filtering and sorting

Use the input fields to build a focused model shortlist:

- `query` searches model IDs, names, providers, and descriptions. Example: `vision`
- `providers` accepts one or more provider IDs. Example: `["openai", "anthropic"]`
- `modalities` requires input support for every selected modality. Example: `["image"]`
- `minContextLength` keeps models with at least the requested context window. Example: `100000`
- `maxInputPricePerMillion` and `maxOutputPricePerMillion` set USD-per-million-token limits
- `freeOnly` keeps models with zero input and output token pricing
- `requiresToolCalling`, `requiresReasoning`, and `requiresStructuredOutput` filter by capabilities
- `includeExpired` includes models whose catalog expiration date has passed
- `sortBy`, `sortDirection`, and `limit` control ordering and result size

Leave filters empty to return the first 1,000 matching records. Set `limit` to `0` to write the full available catalog; full exports are written in batches to keep the run efficient.

### Common uses

- Compare model pricing and context limits across providers
- Find models suitable for vision, audio, video, or long-context workloads
- Build a budget-conscious shortlist for an application
- Feed normalized model metadata into another workflow, spreadsheet, or internal tool

### Output

Results are written to the Actor's default dataset and can be downloaded as JSON, CSV, Excel, or other supported formats. The Output tab includes a readable overview table, while the full records remain available through the dataset API.

### Ready-to-use Tasks

Use these public Tasks as starting points:

- [Browse the full AI model catalog](https://apify.com/fetchfinch/ai-model-catalog/examples/ai-catalog-default)
- [Find long-context OpenAI models](https://apify.com/fetchfinch/ai-model-catalog/examples/ai-catalog-openai)
- [Find free AI vision models](https://apify.com/fetchfinch/ai-model-catalog/examples/ai-catalog-free-vision)
- [Find affordable reasoning models](https://apify.com/fetchfinch/ai-model-catalog/examples/ai-catalog-cheap-reasoning)

### Data freshness

The Actor retrieves model metadata during every run. Provider names, pricing, capabilities, and model availability can change without notice. Use the data for discovery and comparison, then confirm important details with the relevant provider.

# Actor input Schema

## `query` (type: `string`):

Case-insensitive search across model ID, name, provider, and description.

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

Optional provider IDs or names. Leave empty to include all providers.

## `modalities` (type: `array`):

Only return models supporting every listed input modality, such as text, image, audio, video, or file.

## `minContextLength` (type: `integer`):

Minimum context window in tokens.

## `maxInputPricePerMillion` (type: `number`):

Maximum input price in USD per million tokens.

## `maxOutputPricePerMillion` (type: `number`):

Maximum output price in USD per million tokens.

## `freeOnly` (type: `boolean`):

Only return models with both zero input and zero output token price.

## `requiresToolCalling` (type: `boolean`):

Only return models advertising tool calling support.

## `requiresReasoning` (type: `boolean`):

Only return models advertising reasoning support.

## `requiresStructuredOutput` (type: `boolean`):

Only return models advertising structured output support.

## `includeExpired` (type: `boolean`):

Include records whose expiration date has passed.

## `sortBy` (type: `string`):

Sort the output by name, contextLength, inputPrice, or outputPrice.

## `sortDirection` (type: `string`):

Sort output in ascending or descending order.

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

Maximum number of records to write. Defaults to 1000 for reliable runs. Use 0 for all matching records.

## Actor input object example

```json
{
  "freeOnly": false,
  "requiresToolCalling": false,
  "requiresReasoning": false,
  "requiresStructuredOutput": false,
  "includeExpired": false,
  "sortBy": "name",
  "sortDirection": "ascending",
  "limit": 1000
}
```

# Actor output Schema

## `models` (type: `string`):

The normalized model records written to the default dataset.

## `summary` (type: `string`):

Counts, source URL, timestamp, and filters used for this run.

# 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("fetchfinch/ai-model-catalog").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("fetchfinch/ai-model-catalog").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 fetchfinch/ai-model-catalog --silent --output-dataset

```

## MCP server setup

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

```

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/nT9cp5K7qJy8FV4SV/builds/dJUKeCxZBKhZ1J5Mm/openapi.json