GPU Server Rental

GAMING & LIGHT WORKLOAD

Hardware: AMD Radeon RX Vega 7 (integrated) · Ryzen 5 5600G · Tier 3 Istanbul

Game servers: Minecraft (Vanilla/Spigot/Paper), CS 1.6, MTA:SA, Rust (small to mid scale), ARK (low slots), FiveM (small RP servers), Valheim, Terraria, Palworld (low player count), Garry's Mod. As an integrated GPU, player capacity is limited compared to dedicated GPU packages; ideal for testing, hobby and low-budget projects.

Other uses: Low-bitrate streaming with OBS/Streamlabs, Parsec/Moonlight remote desktop, Discord bot hosting, lightweight web panel, small database + game panel (Pterodactyl, AMP) combinations.

Who should choose it? First-time GPU server users, low-player gaming communities, student/hobby projects and those who want to start with a minimum budget.

DEDICATED GPU · GAMING & VISUAL WORK

Hardware: NVIDIA GTX 1050 Ti 4GB (dedicated GPU) · Ryzen 9 5950X · NVENC-enabled video encoding

Game servers: FiveM (mid-scale RP), ARK: Survival Evolved, Rust, 7 Days to Die, Conan Exiles, Palworld, Squad (low to mid slots), Insurgency, CS2 dedicated (small tournaments), Euro Truck Simulator 2 convoy. Dedicated GPU delivers more stable TPS/FPS and higher concurrent player support than Vega packages.

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

Who should choose it? Active gaming community operators, FiveM/ARK/Rust server hosts, small teams running light render or streaming on the same machine.

ENTERPRISE AI · HIGH VRAM

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

AI inference: Running 14B–30B parameter LLMs quantized (Q4/Q8), enterprise chatbot with Llama/Mistral/Qwen family, document summarization, RAG (retrieval-augmented generation) pipelines. 24GB VRAM provides a critical advantage for running large models on a single card.

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

Important note: Tesla P40 is inference-focused; it does not include Tensor Cores. Token/s speed is lower than RTX series but 24GB memory capacity lets you run large models. For intensive model training, RTX 5090 is more suitable.

Who should choose it? Teams building enterprise AI services, those wanting KVKK-compliant local LLM hosting, ML inference projects needing large memory, university/R&D labs.

DUAL GPU · AI & RENDER

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

AI (high throughput): Multi-model concurrent inference (vLLM/Ollama API), ComfyUI batch render, Stable Diffusion XL parallel generation, LoRA fine-tuning experiments. ~2x token/s vs a single card and higher concurrent request capacity.

Render & visual: Blender Cycles dual-GPU render, video AI upscale pipeline, multiple projects at once. Ideal in agency environments when time equals cost.

Who should choose it? Teams offering AI SaaS/API services, agencies needing render farms, high-concurrency projects where a single RTX 5060 Ti is not enough, teams wanting dual GPU for budget/performance balance.

GAMING & MEDIUM WORKLOAD

Hardware: AMD Radeon RX Vega 8 (integrated) · Ryzen 7 5700G · ~15-20% more powerful GPU than Vega 7

Game servers: Minecraft (heavy plugin/modpack), CS2 community servers, Rust (mid scale), ARK, FiveM (mid RP), Project Zomboid, Satisfactory, Enshrouded, Sons of the Forest co-op hosting. Compared to Vega 7, supports more mods, higher view distance and more stable performance.

Other uses: Twitch/YouTube low to mid quality streaming, remote graphics desktop (for designers), small game studio test environment, Discord + panel + game server on the same machine.

Who should choose it? Game server owners where Vega 7 is not enough but dedicated GPU budget is not yet available, communities targeting 20-50 players.

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 for models like Mistral 7B, Llama 13B, Qwen 14B, DeepSeek-Coder with Ollama/llama.cpp. Stable Diffusion / SDXL / FLUX (quantized) image generation. RAG chatbot, code assistant, document analysis, automated summarization pipelines. 16GB VRAM offers ideal capacity to comfortably run 7B-14B models quantized.

Render & media: Blender Cycles, Unreal Engine lightmap, Cinema 4D, DaVinci Resolve / Premiere Pro GPU acceleration, After Effects, 1080p-1440p video render. All CUDA-enabled applications (MATLAB, Octane bench test, etc.).

Who should choose it? AI startups, freelance 3D artists, video editors, developers experimenting with local LLMs, gaming + AI hybrid projects (AI NPC, procedural content).

TOP TIER · 32GB GDDR7

Hardware: NVIDIA RTX 5090 32GB GDDR7 · Ryzen 9 9950X · 1.792 GB/s memory bandwidth · 5th-gen Tensor Cores · FP8/FP4 AI acceleration

AI (top tier): Running large models like Qwen 32B, Gemma 26-31B, Mistral Large quantized Q4 on a single card. Long context (32K-128K+) agentic coding, multi-model concurrent loading, vLLM/Ollama production API service. Fine-tuning experiments (7B-30B LoRA/QLoRA). High-resolution AI image/video pipelines with ComfyUI.

Professional render: 4K+ heavy Blender/Cinema 4D/Unreal scenes, architectural visualization (V-Ray, Enscape), post-production, VR content production. ~30-40% faster render and AI throughput vs RTX 4090.

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

Who should choose it? Agencies, architecture/engineering studios, AI SaaS companies, enterprise projects requiring large model inference, professional teams where time equals money.

DUAL GPU · ENTERPRISE AI

Hardware: 2× NVIDIA RTX 5090 32GB GDDR7 (64GB toplam VRAM) · Ryzen 9 9950X · 5th-gen Tensor Cores · FP8/FP4 AI acceleration · 1.792 GB/s memory bandwidth (per card)

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

Enterprise usage: KVKK-compliant local LLM hosting, enterprise AI platform, architecture/engineering render farm, video production AI pipeline. Maximum throughput beyond a single RTX 5090.

Who should choose it? Teams building enterprise AI services, those wanting KVKK-compliant local LLM hosting, ML inference projects needing large memory, university/R&D labs.