---
type: "post"
stable_id: "post:interconnects-model-artifacts-adoption-dashboard"
slug: "interconnects-model-artifacts-adoption-dashboard"
title: "Interconnects Turns Model Releases Into A Longitudinal Adoption Dataset"
description: "Interconnects launched an Artifacts Hub covering 792 models and an Adoption Dashboard that tracks downloads and derivatives over time."
retrieval_nugget: "The value is data joining: capability, inference usage, downloads, derivatives, similarity, geography, and organization become one longitudinal view rather than isolated leaderboards."
published_at: "2026-08-03"
updated_at: "2026-08-05"
record_date: "2026-08-03"
date_kind: "published_at"
topics: ["open-models","adoption","model-evaluation","market-intelligence"]
entities: ["Interconnects","Hugging Face","OpenRouter","Artificial Analysis"]
source_urls: ["https://interconnects.ai/p/introducing-our-artifacts-hub-and"]
source_format: "article"
editorial_timing: {"lane":"regular_hourly_analysis","scheduled_at":"2026-08-07T13:00:00+03:00","real_news_delta":"analytical follow-up"}
visual_decision: {"status":"not_applicable","reason":"the source product is already a visual dashboard; a generated diagram would duplicate rather than clarify the evidence surface","reviewed_by":"codex"}
schema_version: "newruntime-agent-readable-v0.2"
status: "published"
visuals: []
routes: {"html":"https://newruntime.com/posts/interconnects-model-artifacts-adoption-dashboard/","markdown":"https://newruntime.com/posts/interconnects-model-artifacts-adoption-dashboard.md","json":"https://newruntime.com/posts/interconnects-model-artifacts-adoption-dashboard.json"}
---

# Interconnects Turns Model Releases Into A Longitudinal Adoption Dataset

## Retrieval answer

The value is data joining: capability, inference usage, downloads, derivatives, similarity, geography, and organization become one longitudinal view rather than isolated leaderboards.

Interconnects launched an Artifacts Hub covering 792 models released over the last two years and an Adoption Dashboard that updates model download and derivative activity daily.

The hub combines curated Hugging Face model records with OpenRouter inference-token data, Artificial Analysis capability measurements, RAM and adoption signals, and VAIL similarity measures. The adoption view can be explored by geography and organization and is intended to make shifts such as the US-China open-model gap visible over time.

The useful move is from launch-day ranking to longitudinal evidence. A model can score well but attract little deployment, or spread through derivatives and downstream usage without remaining at the top of a benchmark. Joining those dimensions makes the ecosystem easier to analyze as a market and a technical lineage.

The dashboard is itself an editorial source, not proof of causality. Downloads, tokens, derivatives, and geography each have measurement bias. Their value comes from consistent definitions, visible provenance, and comparison across time.