> ## Documentation Index
> Fetch the complete documentation index at: https://docs.coreweave.com/llms.txt
> Use this file to discover all available pages before exploring further.

# A100

> Specifications, pricing, and availability for the A100 GPU instance

These instances are powered by eight NVIDIA A100 Tensor Core GPUs, each providing 80 GB of high-bandwidth HBM2e memory. As a foundational accelerator for the previous generation of AI, these are versatile instances that deliver excellent performance for mixed-precision workloads. The GPUs are interconnected with NVIDIA NVLink, making them a powerful and proven choice for distributed training. Their configuration offers a cost-effective solution for a wide range of demanding AI and data analytics tasks.

## Specifications

| Feature              | Detail                                                                                                     |
| :------------------- | :--------------------------------------------------------------------------------------------------------- |
| **Category**         | Professional AI & Graphics                                                                                 |
| **Instance ID**      | `gd-8xa100-i128`                                                                                           |
| **GPU**              | 8x NVIDIA A100                                                                                             |
| **GPU RAM**          | 80 GB                                                                                                      |
| **GPU Connectivity** | NVLink                                                                                                     |
| **CPU Model**        | Intel Ice Lake 8358 (2.60 GHz)                                                                             |
| **vCPUs**            | 128                                                                                                        |
| **RAM**              | 2048 GB                                                                                                    |
| **Local Storage**    | 7.68 TB                                                                                                    |
| **Network Speed**    | Single-port 100GbE                                                                                         |
| **Availability**     | [**RNO2A**](/platform/regions/us-west#rno2a)<br />[**US-EAST-04A**](/platform/regions/us-east#us-east-04a) |

## Primary use cases

AI model training, high-performance inference, and various HPC applications including scientific simulations.

## Recommended models

Training models up to 40B parameters such as Gemma 4 31B; a standard choice for fine-tuning most mid-sized open-source models. For inference, they can handle models up to 40B, such as Qwen 3.6 35B-A3B, on a per-GPU basis or a single instance of a quantized larger model such as Qwen 3.5 397B-A17B utilizing tensor parallelism.