GPU Server Rental | Physical Server with a Graphics Card

DISCRETE GPU · GAMING & VISUAL WORK

Hardware: NVIDIA RTX 5060 8GB (discrete GPU) · Ryzen 9 5950X · NVENC-accelerated video encoding

Game servers: FiveM (mid-size RP), ARK: Survival Evolved, Rust, 7 Days to Die, Conan Exiles, Palworld, Squad (low-to-mid slot), Insurgency, CS2 dedicated (small tournaments), Euro Truck Simulator 2 convoy. Thanks to the discrete GPU it offers more stable TPS/FPS and higher concurrent player support than integrated GPUs.

Visual & media: Light Blender/Cinema 4D scenes, HandBrake/FFmpeg video conversion, live stream recording with OBS NVENC, low-resolution render jobs for small studios.

Who is it for? Those running an active gaming community or a FiveM/ARK/Rust server, and small teams doing light rendering or streaming on the same machine.

ENTERPRISE AI · HIGH VRAM

Hardware: NVIDIA Tesla P40 24GB GDDR5 · 2× Xeon E5-2680 v4 · INT8 inference optimisation · Headless (no display output)

AI inference: Running quantized (Q4/Q8) LLMs with 14B–30B parameters, enterprise chatbots with the Llama/Mistral/Qwen families, document summarisation and RAG (retrieval-augmented generation) pipelines. 24GB of VRAM is a key advantage for running large models on a single card.

Deep learning & vision: Image classification, object detection (YOLO), OCR, anomaly detection, NLP sentiment analysis and recommendation systems with PyTorch/TensorFlow. Stable Diffusion SDXL (quantized) image generation. Video analysis pipelines (DeepStream-style workloads).

Important note: The Tesla P40 is inference-focused and has no Tensor Cores. Its token/s speed is lower than the RTX series, but its 24GB memory capacity lets it run large models. The RTX 5090 is better suited to heavy model training.

Who is it for? Teams building enterprise AI services, those who want to host a KVKK-compliant local LLM, ML inference projects with large memory needs, and university/R&D labs.

DUAL GPU · AI & RENDER

Hardware: 2× NVIDIA RTX 5060 Ti 16GB (32GB total VRAM) · Ryzen 9 9950X · NVENC/Tensor Core · parallel CUDA workloads

AI (high throughput): Concurrent multi-model inference (vLLM/Ollama API), ComfyUI batch rendering, parallel Stable Diffusion XL generation, LoRA fine-tuning experiments. About 2× the token/s of a single card and higher concurrent request capacity.

Rendering & visual: Blender Cycles dual-GPU rendering, video AI upscale pipelines, several projects at once. Ideal when time = cost in an agency setting.

Who is it for? AI SaaS/API providers, agencies that need a render farm, high-concurrency projects for which a single RTX 5060 Ti is not enough, and teams that want dual GPUs at a balanced budget/performance.

AI INFERENCE & RENDER

Hardware: NVIDIA RTX 5060 Ti 16GB GDDR7 · Ryzen 9 9950X · Blackwell architecture · 5th-gen Tensor Cores · 4th-gen RT Cores · DLSS 4

AI: Local inference of models such as Mistral 7B, Llama 13B, Qwen 14B and DeepSeek-Coder with Ollama/llama.cpp. Stable Diffusion / SDXL / FLUX (quantized) image generation. RAG chatbots, coding assistants, document analysis and automatic summarisation pipelines. 16GB of VRAM is an ideal capacity for running 7B–14B models comfortably when quantized.

Rendering & media: Blender Cycles, Unreal Engine lightmaps, Cinema 4D, DaVinci Resolve / Premiere Pro GPU acceleration, After Effects, 1080p–1440p video rendering. All CUDA-enabled applications (MATLAB, Octane benchmarks, etc.).

Who is it for? AI startups, freelance 3D artists, video editors, developers who want to try local LLMs, and hybrid gaming + AI projects (AI NPCs, procedural content).

TOP TIER · 32GB GDDR7

Hardware: NVIDIA RTX 5090 32GB GDDR7 · Ryzen 9 9950X · 1,792 GB/s bandwidth · 5th-gen Tensor Cores · FP8/FP4 AI acceleration

AI (high end): Running large models such as Qwen 32B, Gemma 26–31B and Mistral Large with Q4 quantization on a single card. Long-context (32K–128K+) agentic coding, loading several models at once, production vLLM/Ollama API services. Fine-tuning experiments (7B–30B LoRA/QLoRA). High-resolution AI image/video pipelines with ComfyUI.

Professional rendering: Heavy 4K+ Blender/Cinema 4D/Unreal scenes, architectural visualisation (V-Ray, Enscape), post-production, VR content creation. About 30–40% faster rendering and AI throughput than the RTX 4090.

Gaming (high performance): High-slot FiveM, large ARK/Rust clusters, heavy modded Minecraft servers — although this plan is positioned primarily for AI and professional rendering.

Who is it for? Agencies, architecture/engineering studios, companies building AI SaaS, enterprise projects that need large-model inference, and professional teams for whom time = money.

DUAL GPU · ENTERPRISE AI

Hardware: 2× NVIDIA RTX 5090 32GB GDDR7 (64GB total VRAM) · Ryzen 9 9950X · 5th-gen Tensor Cores · FP8/FP4 AI acceleration · 1,792 GB/s bandwidth (per card)

AI (high end): Running quantized 70B+ models, long-context agentic coding, production LLM APIs (high concurrency), multi-GPU tensor parallelism. Fine-tuning (7B–70B LoRA/QLoRA) and large-batch inference.

Enterprise use: KVKK-compliant local LLM hosting, enterprise AI platforms, architecture/engineering render farms, video production AI pipelines. Maximum throughput beyond a single RTX 5090.

Who is it for? Companies building enterprise AI infrastructure, projects that need large-model inference, agency render farms, time-critical production teams and anyone who needs GPUs at platform scale.