AMD EPYC 7413 + T4 Dedicated Server
Bare-metal AMD EPYC 7413 + T4 dedicated servers with full root access and dedicated hardware in United Kingdom. one ready-to-deploy configuration covering 48 cores, 128GB RAM, deployed with unmetered bandwidth and 24/7 support.
- 99.99%Network Uptime
- UnmeteredBandwidth
- InstantSetup
- 24/7Expert Support
- AMD7413
- Up to128 GB
- Up to2x 960GB SSD MU
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Configure your ideal AMD EPYC 7413 + T4 dedicated server and deploy in minutes.
Instant Setup
Your server will be ready in 1–2 business days.
Available AMD EPYC 7413 + T4 Servers
| Selected | Server | Location | CPU | RAM | Storage | Bandwidth / Port | Price /mo | Action |
|---|---|---|---|---|---|---|---|---|
| Dell R7525 (16SFF+8NVMe) 2x AMD EPYC 7413 - T4 |  United Kingdom | Dual x AMD EPYC 7413 (48 cores) | 128 GB | 2x 960GB SSD MU | — | $560.52 |
AMD EPYC 7413 + T4 use cases and scoring
MonoVM Server Score
6.8/10
Hardware index from 48 cores, 128 GB max RAM, SSD storage, 1 location. Not a customer rating.
Best For
- CUDA inference for models and batches that fit 16 GB per T4.
- Computer-vision services with significant CPU decoding and preprocessing.
- H.264 or HEVC media pipelines supported by the chosen T4 software stack.
- Existing inference applications already tested on T4 hardware.
Not Ideal For
- Models needing more than 16 GB GPU-local memory without quantization, offloading or supported distribution.
- Hardware AV1 encoding, which is not a T4 encoder feature.
- Large training workloads assuming a forty-eight-core CPU host makes the T4 equivalent to a larger GPU.
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AMD EPYC 7413 + T4 Specifications
- Processor
- AMD EPYC 7413 + T4
- Vendor
- AMD
- Product line
- EPYC
- Cores
- 48
- Memory
- 128 GB
- GPU
- T4
- Storage options
- 2x 960GB SSD MU
- Configurations
- 1
- Locations
- 1
- Root access
- Full root / administrator
Network & Locations
Every AMD EPYC 7413 + T4 ships on a dedicated uplink with unmetered bandwidth, DDoS filtering and 24/7 monitoring.
- United Kingdom
Frequently Asked Questions
Answers to common questions about AMD EPYC 7413 + T4 servers.
The listed server pairs two EPYC 7413 CPUs, giving 48 physical cores, with 128 GB RAM, two 960 GB SSDs and an NVIDIA T4. Each T4 has 16 GB GPU memory. Confirm the GPU count and a supported driver and framework combination.
It is a candidate for supported CUDA inference workloads that fit its 16 GB memory budget. Check the model precision, batch size, context length and framework support. Measure latency and throughput on the actual model instead of using parameter count alone.
No. T4 does not provide hardware AV1 encoding. For media applications, verify the supported H.264 or HEVC path and benchmark the intended quality and stream settings. If AV1 encoding is required, compare a GPU that explicitly supports it.
Compare L4 for 24 GB per GPU and hardware AV1 encoding, or when your measured inference workload needs a different performance profile. The CPU host can be similar, so focus on the accelerator and exact software requirements.
System RAM and GPU memory are separate. Some runtimes support CPU offloading, but that changes latency, throughput and software requirements. Test the full workload with its cache and temporary allocations rather than adding host RAM to the GPU memory figure.
The host can run preprocessing, data ingestion and application services around the GPU stage. Whether those cores are useful depends on the pipeline. Measure CPU work and GPU utilization; extra host cores do not increase the T4 memory or compute resources.