Ollama Model Library API
The full Ollama model library as structured JSON - model name, pull count, sizes, capabilities, and last update.
What this feed does
Ollama's library is the de-facto leaderboard of local LLM adoption - but it is a web page, not an API. This feed scrapes the full library on demand and returns every model as structured JSON, including its pull count (the demand signal).
Structured, not scraped-by-you
Clean JSON with stable field names - no HTML parsing, no selectors to maintain when the site changes.
Pay only for what you pull
No subscription. $0.005 per record via Apify's metered billing; a typical pull is cents.
Human + agent ready
Call it from cURL, Python, or JS - or hand it to an AI agent as an MCP tool.
Always the latest
Scraped from the official source on every run, so you never ship stale data.
What each record contains
Every result is a JSON object with these fields.
| Field | Type | Description |
|---|---|---|
name | string | Model name (e.g. llama3.3, qwen2.5). |
pulls | string | Total pull count - the adoption signal. |
sizes | string | Available parameter sizes (first listed). |
capabilities | string | Capability tag (tools, vision, embedding, ...). |
tag_count | string | Number of published tags/variants. |
updated | string | Relative last-update time. |
description | string | Model description. |
url | string, URL | Link to the model page on ollama.com. |
Live sample
The most recent records, straight from the feed. Live sample - fetched at build time
| name | pulls | sizes | updated |
|---|---|---|---|
| llama3.1 | 117.2M | 8b | 1 year ago |
| deepseek-r1 | 89.8M | 1.5b | 1 year ago |
| nomic-embed-text | 78.5M | 2 years ago | |
| llama3.2 | 76.6M | 1b | 1 year ago |
| gemma3 | 38.6M | 270m | 11 months ago |
| qwen2.5 | 34.7M | 0.5b | 1 year ago |
| qwen3 | 32.3M | 0.6b | 9 months ago |
| mistral | 31.1M | 7b | 1 year ago |
Call it in one line
Runs the actor and returns the dataset. Swap in your Apify token.
curl "https://api.apify.com/v2/acts/zenolvepro~ollama-library/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN"
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("zenolvepro/ollama-library").call()
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
print(row)import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('zenolvepro/ollama-library').call();
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);https://mcp.apify.com?tools=zenolvepro/ollama-library
Point any MCP-capable agent at this endpoint and the feed becomes a callable tool.
Who uses it
AI VCs, devtool marketers, and ML-infra vendors sizing open-model demand use it for monitoring, benchmarking, alerting, and enrichment.
Pricing
Billed through Apify. A tiny per-run start fee ($0.00005) applies. Only pay for records you actually pull.