Pricing

from $5.00 / 1,000 results

Ollama Model Library Scraper

Full Ollama model library feed: model name, pull count, tag count, parameter sizes, capabilities, description and last-updated date. Track which open LLMs gain traction. For AI VCs, devtool marketers and ML-infra vendors sizing model demand. Pay per result.

Pricing

from $5.00 / 1,000 results

Rating

0.0

(0)

Developer

Zenolve

Actor stats

Bookmarked

Total users

Monthly active users

3 hours ago

Last modified

Categories

You can access the Ollama Model Library Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "url": "https://ollama.com/library",
10    "itemSelector": "#repo li",
11    "fields": {
12        "name": "div[title]::attr(title)",
13        "url": "a::attr(href)",
14        "description": "p.max-w-lg::text",
15        "pulls": "p.my-4 > span:nth-of-type(1) > span:nth-of-type(1)::text",
16        "tag_count": "p.my-4 > span:nth-of-type(2) > span:nth-of-type(1)::text",
17        "updated": "p.my-4 > span:nth-of-type(3) > span:nth-of-type(2)::text",
18        "capabilities": "span.bg-indigo-50::text",
19        "sizes": "span.text-blue-600::text",
20    },
21    "proxy": { "useApifyProxy": True },
22}
23
24# Run the Actor and wait for it to finish
25run = client.actor("zenolvepro/ollama-library").call(run_input=run_input)
26
27# Fetch and print Actor results from the run's dataset (if there are any)
28print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
29for item in client.dataset(run["defaultDatasetId"]).iterate_items():
30    print(item)
31
32# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Ollama Model Library Scraper API in Python

The Apify API client for Python is the official library that allows you to use Ollama Model Library Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Ollama Model Library Scraper API in JavaScript

Ollama Model Library Scraper API through CLI

Ollama Model Library Scraper OpenAPI definition

Ollama Model Library Scraper API

Ollama Library Scraper

automation-lab/ollama-library-scraper

Scrape the Ollama model library. Get model names, pull counts, parameter sizes, capabilities, and update dates. No API needed.

Stas Persiianenko

Ollama Library Scraper - Local LLM Model Data

benthepythondev/ollama-library-scraper

Scrape Ollama Library pages and extract local LLM model names, URLs, descriptions and AI model metadata.

Ben

HuggingFace Model Scraper - AI/ML Model Data

jungle_synthesizer/huggingface-model-scraper

Scrape AI/ML model metadata from the HuggingFace Hub. Extract model names, task types, download counts, likes, libraries, authors, tags, licenses, model sizes, and model card excerpts. Filter by task type, library, author, and search query.

BowTiedRaccoon

Ollama Apify Mcp

lenticular_negative/ollama-apify-mcp

The Ollama MCP Actor brings together Apify’s web-scraping power with fast, private, on-device AI. No external APIs required. It lets you run local LLMs through Ollama using the Model Context Protocol, so you can analyze scraped data, extract insights, and generate responses with full control.

Anwesh Mishra

Hugging Face Model Explorer

lovely_radiologist/hf-model-explorer

Structured export of HF models with task, library, license, download count, and parsed model-card metadata. Built for AI teams doing model selection at scale.

Vivek Gaur

Hugging Face Models Scraper - Cheap 🤗🤖🔎

scrapestorm/hugging-face-models-scraper---cheap

🟠 Easily collect Models from Hugging Face Provide one or multiple search keywords and extract structured model data including model name, owner, likes, downloads, tags, last update date, match count & more 🤖📊 Perfect for AI model research, popularity tracking & model ecosystem monitoring 🚀

Storm_Scraper

5.0

Hugging Face Models Scraper - Low-cost💲🔥🤖📌

delectable_incubator/hugging-face-models-scraper-low-cost

Scrape Hugging Face model listings 🤖📊 with a powerful AI model scraper. Extract model names, creators, downloads, likes, tags, update dates, model URLs, and popularity metrics from keyword searches. Ideal for AI research, model discovery, ecosystem monitoring and machine learning datasets 🚀

Prime Scrape

Ai Model Pricing Availability

haehnchen/ai-model-pricing-availability

Compare AI model prices across providers. Find where a LLM model is available and compare input/output pricing.

Haehnchen

Replicate Models Scraper - AI Model Directory Data

benthepythondev/replicate-models-scraper

Scrape Replicate Explore pages and extract AI model names, URLs, creators, descriptions and model marketplace metadata.

Ben

Huggingface Models

david_flagg/huggingface-models

Scrape model metadata from HuggingFace Hub — the largest open-source ML model registry. Get downloads, likes, trending scores, licenses, tags, and architecture info for 1M+ models. Filter by task type, ML library, or author. Uses the official HF API — no auth required.