AI Hosting & Infrastructure
AI Hosting & Infrastructure
Build production AI infrastructure on dedicated GPU servers. These guides cover networking, storage architecture, scaling strategies, and deployment patterns for running AI workloads on bare metal. From private AI hosting to multi-GPU clusters, learn how to architect GPU infrastructure that scales.
Scaling Inference Horizontally vs Vertically
Bigger card or more cards - the oldest infrastructure question, applied specifically to LLM inference in 2026.
SGLang vs vLLM in 2026 – Production Comparison
Both engines claim best-in-class throughput. Running them side-by-side on identical hardware reveals where each actually wins.
Splitting Embedding and LLM Across Two GPUs
In a RAG stack the embedder and the LLM compete for VRAM and compute. Putting them on different cards solves…
Tensor Parallelism vs Pipeline Parallelism on Dedicated GPU Servers
The two ways to split a large model across multiple GPUs. When to use which, with concrete numbers from vLLM…
Two RTX 6000 Pro Architecture Patterns
192GB of VRAM across two cards. The serving patterns that justify this much capacity and the ones that do not.
Virtual GPU Partitioning for Inference – Options and Tradeoffs
vGPU, MIG, MPS, and plain CUDA device selection - a plain-English guide to how GPUs get sliced up for multi-workload…
1 GPU vs 2 GPU: When Does Multi-GPU Make Sense?
Understand when scaling from one GPU to two GPUs makes sense for AI inference, including throughput gains, latency trade-offs, and…
GPU Capacity Planning for AI SaaS Products
Step-by-step GPU capacity planning for AI SaaS — sizing GPUs for chatbots, APIs, image generation, and voice agents based on…
Model Sharding: Run 70B+ Models Across Multiple GPUs
A practical guide to sharding 70B+ parameter models across multiple GPUs, covering VRAM requirements, sharding strategies, configuration examples, and performance…
Tensor Parallelism vs Pipeline Parallelism for Multi-GPU
Understanding tensor parallelism and pipeline parallelism for multi-GPU LLM inference, including architecture diagrams, configuration examples, and scaling benchmarks.
Explore GPU Hosting Solutions
From the blog to your next deployment — pick the right platform for your workload.
Dedicated GPU Hosting
Bare-metal servers with a dedicated GPU, NVMe, full root access, and 1Gbps networking from our UK datacenter.
Browse GPU ServersPrivate AI Hosting
Isolated GPU infrastructure for sensitive AI workloads — no shared hardware, full data control.
Explore Private AIMulti-GPU Clusters
Scale horizontally with multi-GPU configurations for training and large-model inference.
Explore ClustersAPI Hosting
Host your own AI API endpoints on dedicated GPU servers — low latency, high availability.
Explore API HostingOpen Source LLM Hosting
Deploy LLaMA, Mistral, DeepSeek, and more on dedicated hardware with no per-token API fees.
Explore LLM HostingTokens/sec Benchmarks
Real-world tokens per second data across every GPU we offer, tested on popular LLMs.
View BenchmarksReady to deploy your AI workload?
Dedicated GPU servers from our UK datacenter. NVMe storage, 1Gbps networking, full root access.
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PE7 1XU, England
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