Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Host your own AI video generation platform on a dedicated GPU server using models like Wan-AI, CogVideoX, and Mochi for text-to-video, image-to-video, and video editing workflows.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Build a high-throughput document OCR pipeline on a dedicated GPU server using PaddleOCR, Tesseract, and AI-powered post-processing for accurate text…
Build a real-time AI content moderation system on a dedicated GPU server using vision models, text classifiers, and multi-modal analysis…
Learn how to build a production-ready AI-powered search engine on a dedicated GPU server using vector embeddings, semantic search, and…
Secure your self-hosted AI inference API with API key authentication, JWT tokens, rate limiting, and IP whitelisting. Production-ready configurations for…
Learn how to benchmark your GPU server for AI inference and training workloads. Covers LLM throughput testing, CUDA compute benchmarks,…
Build an auto-scaling AI inference architecture with load balancing across multiple GPU servers. Covers health checks, dynamic scaling triggers, and…
Set up comprehensive GPU monitoring on your dedicated server using nvidia-smi, Prometheus, Grafana, and DCGM. Track VRAM usage, temperature, power…
Learn how to run GPU-accelerated AI workloads in Docker containers using the NVIDIA Container Toolkit. Covers installation, docker-compose with GPU…
Configure Nginx as a reverse proxy for AI inference APIs running on vLLM, Ollama, or custom servers. Covers TLS termination,…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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Browse ArticlesDedicated GPU servers from our UK datacenter. NVMe storage, 1Gbps networking, full root access.