# Node Requirements

**Node Types and Specifications**

<figure><img src="/files/1qtcJPBXHD6iyFaS77k3" alt=""><figcaption></figcaption></figure>

1. **GPU Nodes**:
   * **Purpose**: Optimized for AI workloads requiring high-performance GPUs, such as training and inference.
   * **Use Cases**:
     * **AI Training**: Handles compute-intensive tasks like deep learning model training.
     * **Inference**: Processes real-time predictions and fine-tuning tasks.
   * **Specifications**:
     * **Minimum**: NVIDIA T4, 16GB VRAM, 64GB system RAM.
     * **Recommended**: NVIDIA A100, 80GB VRAM, 128GB system RAM, NVMe SSD.
2. **CPU Nodes**:
   * **Purpose**: Designed for general-purpose compute tasks, including orchestration, lightweight AI workloads, and preprocessing.
   * **Use Cases**:
     * **General Compute**: Runs lightweight tasks and supports distributed workloads.
     * **Memory Optimized**: Handles tasks requiring significant system memory.
   * **Specifications**:
     * **Minimum**: 4 CPU cores, 8GB RAM.
     * **Recommended**: 32 CPU cores, 128GB RAM.
3. **Storage Nodes**:
   * **Purpose**: Provides scalable and high-capacity storage for datasets, model checkpoints, and logs.
   * **Use Cases**:
     * **High Capacity**: Supports archival and long-term data storage.
     * **High Performance**: Enables fast access to training data and intermediate results.
   * **Specifications**:
     * **Minimum**: 1TB HDD, 100GB SSD.
     * **Recommended**: 10TB HDD, 2TB NVMe SSD.

***

**Key Features**

* **Flexibility**:
  * Accommodates a variety of workloads with GPU, CPU, and storage-optimized nodes.
* **Scalability**:
  * Supports seamless addition of nodes to meet growing demand for AI workloads.
* **High Performance**:
  * Ensures efficient execution of training, inference, and data processing tasks.

***

**Benefits**

* **Efficiency**: Tailored nodes maximize resource utilization for specific tasks.
* **Reliability**: Robust hardware specifications ensure consistent performance across workloads.
* **Scalability**: Nodes can be upgraded or scaled horizontally to accommodate more complex workloads.
* **Cost Optimization**: Allows providers to contribute resources based on their strengths, optimizing overall operational costs.

Swarm’s **Node Requirements** ensure a balanced and efficient infrastructure capable of supporting diverse AI tasks while delivering high performance and reliability.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://agiledger.gitbook.io/swarmai/technical-specifications/node-requirements.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.