AMD Ryzen 5950X + RTX 3090 Dedicated Server
Bare-metal AMD Ryzen 5950X + RTX 3090 dedicated servers with full root access and dedicated hardware in France and Netherlands. one ready-to-deploy configuration covering 16 cores, 128GB RAM, deployed with unmetered bandwidth and 24/7 support.
- 99.99%Network Uptime
- UnmeteredBandwidth
- InstantSetup
- 24/7Expert Support
- AMD5950X
- Up to128 GB
- Up to1000 GB
Build Your Server
Configure your ideal AMD Ryzen 5950X + RTX 3090 dedicated server and deploy in minutes.
Instant Setup
Your server will be ready in 1–2 business days.
Available AMD Ryzen 5950X + RTX 3090 Servers
| Selected | Server | Location | CPU | RAM | Storage | Bandwidth / Port | Price /mo | Action |
|---|---|---|---|---|---|---|---|---|
| Ryzen 5950x/128/1Tb nvme + RTX 3090 |  Netherlands+1 more | AMD Ryzen 5950X | 128 GB | 1000 GB | — | $456.17 |
AMD Ryzen 5950X + RTX 3090 use cases and scoring
MonoVM Server Score
4.4/10
Hardware index from 16 cores, 128 GB max RAM, 2 locations. Not a customer rating.
Best For
- Quantized LLM inference whose weights, KV cache and runtime buffers fit within 24 GB GPU memory.
- Stable Diffusion and similar image-generation workloads with measured resolution and batch settings.
- CUDA or OptiX rendering for scenes that fit the GPU memory budget.
- PyTorch development and fine-tuning experiments validated for the selected CUDA stack.
- CPU-assisted data preparation that can use sixteen Ryzen cores alongside the GPU.
Not Ideal For
- Large models requiring more than 24 GB on one GPU without supported offloading or sharding.
- Hardware AV1 encoding, which the RTX 3090 does not provide.
- FP64-focused scientific workloads chosen without verifying GPU arithmetic performance.
- Large dataset archives that exceed the listed 1 TB local NVMe allocation.
Compare This Server
Need More Power? Explore Similar Servers
AMD Ryzen 5950X
- 16 Cores
- Up to 128 GB RAM
From $939.90/mo
View DetailsAMD Ryzen 7950X
- 16 Cores
- Up to 128 GB RAM
From $271.70/mo
View DetailsAMD Ryzen 9950X
- 16 Cores
- Up to 128 GB RAM
From $357.50/mo
View DetailsAMD EPYC 7313P
- 16 Cores
- Up to 512 GB RAM
From $1597.19/mo
View Details
AMD Ryzen 5950X + RTX 3090 Specifications
- Processor
- AMD Ryzen 5950X + RTX 3090
- Vendor
- AMD
- Product line
- Ryzen
- Cores
- 16
- Memory
- 128 GB
- GPU
- RTX 3090
- Storage options
- 1000 GB
- IP addresses
- 1 Free
- Configurations
- 1
- Locations
- 2
- Root access
- Full root / administrator
Network & Locations
Every AMD Ryzen 5950X + RTX 3090 ships on a dedicated uplink with unmetered bandwidth, DDoS filtering and 24/7 monitoring.
France- Netherlands
Frequently Asked Questions
Answers to common questions about AMD Ryzen 5950X + RTX 3090 servers.
The listed plan pairs a 16-core, 32-thread Ryzen 9 5950X with 128 GB RAM, 1 TB NVMe storage and an RTX 3090. Each RTX 3090 has 24 GB GPU memory. Confirm the selected server configuration and accelerator quantity before deployment.
Model fit depends on precision, quantization, context length, batch size and runtime overhead. Budget for weights, KV cache and temporary buffers within 24 GB. Test the exact model and serving runtime; a parameter count or the host 128 GB RAM does not guarantee GPU fit.
Use versions whose support includes RTX 3090, with a compatible NVIDIA driver and CUDA-enabled framework or container. Validate a representative job at the intended resolution and batch size. The hardware listing does not guarantee preinstalled software, models or managed troubleshooting.
Compare the RTX 4090 configuration for its newer GPU architecture, hardware AV1 encoding and measured application performance. Both GPUs have 24 GB memory, so switching to a 4090 does not by itself solve a workload that needs more VRAM.
RTX 3090 supports hardware AV1 decoding but not hardware AV1 encoding. Check the media application and driver for the exact decoding or H.264/HEVC encoding path you need. For AV1 output, compare a GPU with an AV1 hardware encoder.
Use CPU workers for supported preprocessing and data loading, system RAM for host-side caches, and GPU memory for GPU-resident computation. Tune worker count and batch size together. These resources are separate; adding host RAM does not automatically enlarge the 24 GB GPU allocation.