RedSwitches 2x AMD EPYC 7413, $ 496.51/mo. on Linux Dedicated

2 x AMD EPYC 7413 with 48 Cores/96 Threads and a T4 GPU is an AI focused dedicated configuration aimed at teams running model training, fine tuning jobs or high volume inference services. The server is equipped with 128GB of RAM and a storage layout of 2x960GB SSD, giving space for datasets, checkpoints and container images while keeping read and write latency low for GPU bound workloads.
Network connectivity is provisioned at 1 Gbps with a monthly traffic allocation of 30TB, which supports synchronizing data from object storage, streaming training metrics and serving responses from deployed models. This system is hosted in Netherlands and is advertised with an estimated delivery time of 5 days, making it suitable for projects that need predictable provisioning rather than fully elastic cloud instances.
Pricing for this AI server reflects a discounted recurring rate compared to the standard list price, providing better value for long running experiments and production deployments. It offers a balanced mix of CPU throughput, GPU capability and memory, making it versatile for computer vision pipelines, recommendation engines, chat style assistants and other modern machine learning applications.

AI dedicated servers from this provider combine bare metal CPU platforms with modern data centre GPUs to support deep learning training, fine tuning, large language models and low latency inference services. Configurations are available in multiple global regions so workloads can be placed close to end users or data sources.
Each server is delivered with full root access so engineering teams can choose their preferred Linux distribution, GPU driver versions, container runtimes and frameworks such as PyTorch or TensorFlow. The infrastructure is backed by an uptime service level agreement and built in DDoS protection on the network edge, which helps keep public APIs and dashboards available even during hostile traffic events.
Bandwidth allocations are sized for moving large datasets and model checkpoints, and private networking options allow teams to link AI nodes to databases, caching tiers or storage backends securely. Around the clock technical support is available by live chat, tickets and phone, and flexible billing with multiple payment methods makes it easy for organizations to scale clusters up or down as new projects, experiments or production deployments are launched.