> ## Documentation Index
> Fetch the complete documentation index at: https://protocol.crunchdao.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Crunch Nodes
> The services you build and host to run your competition — data ingestion, model orchestration, scoring, and reporting.
A **Crunch Node** is the set of services you build and host to run your Crunch. It contains
your competition logic — how data flows in, how models are called, how predictions are scored, and
how results are reported.
Your Crunch Node relies on [**Model Nodes**](/core-concepts/model-nodes) to execute participant
models remotely. You never run or manage models directly — you call them over the network via the
Model Runner Client.
## What a Crunch Node does
In practice, your node handles four responsibilities:
1. **Data ingestion** — collect or host the data your competition needs (market feeds, datasets,
APIs)
2. **Model orchestration** — send data to connected models, trigger training and inference, and
collect predictions
3. **Scoring** — evaluate predictions against ground truth using your scoring function, aggregate
results, and build a leaderboard
4. **Reporting** — expose results via API so the dashboard, participants, and external systems can
consume them
## Infrastructure requirements
You are responsible for hosting your Crunch Node and everything around it: which data to use,
when to trigger calls, how to compute scores, and how to produce results.
A simple cloud server or on-premises machine is usually enough. The required capacity depends
primarily on what you do **around** predictions — ingestion, scoring, aggregation, and storage.
You do **not** need to size infrastructure for model execution. Models are deployed, scaled, and
managed by Crunch Labs through the [Model Nodes](/core-concepts/model-nodes).
The `crunch-node` package provides a production-ready engine with all four responsibilities
built in. You configure behavior through environment variables and a `CrunchConfig`. See the
[Getting started](/getting-started/local-environment-setup) guide.
Understand the managed infrastructure that executes participant models securely.
## Infrastructure requirements
You are responsible for hosting your Crunch Node and everything around it: which data to use,
when to trigger calls, how to compute scores, and how to produce results.
A simple cloud server or on-premises machine is usually enough. The required capacity depends
primarily on what you do **around** predictions — ingestion, scoring, aggregation, and storage.
You do **not** need to size infrastructure for model execution. Models are deployed, scaled, and
managed by Crunch Labs through the [Model Nodes](/core-concepts/model-nodes).