Tutorials
Hands-on deployment guides for AI frameworks, tools, and pipelines on dedicated GPU servers. Set up PyTorch, TensorFlow, vLLM, and more from scratch — full root access on bare metal.
Migrate from AWS Bedrock to Dedicated GPU: Real-Time Inference Guide
Move your real-time AI inference from AWS Bedrock to dedicated GPU hardware, achieving sub-100ms first-token latency without Bedrock's unpredictable throttling.
Migrate from Azure OpenAI to Dedicated GPU: Copilot Integration Guide
Replace your Azure OpenAI-powered copilot with a self-hosted model on dedicated GPU, removing Microsoft's per-token fees and gaining full control…
Migrate from Azure OpenAI to Dedicated GPU: Customer Service Bot Guide
Replace your Azure OpenAI customer service bot with a self-hosted solution on dedicated GPU, eliminating Microsoft's token markup while handling…
Migrate from Azure OpenAI to Dedicated GPU: Content Moderation Guide
Move your AI content moderation from Azure OpenAI to a dedicated GPU, gaining customisable safety rules and eliminating per-request moderation…
Migrate from RunPod to Dedicated GPU: Multi-Model Serving
Consolidate multiple RunPod pods into a single dedicated GPU server for multi-model serving, eliminating per-pod overhead and achieving lower latency…
Migrate from Lambda to Dedicated GPU: Research Training
Transition your ML research training workloads from Lambda Cloud to dedicated GPUs for persistent environments, faster iteration cycles, and predictable…
Migrate from Lambda to Dedicated GPU: Batch Inference
Move your batch inference pipelines from Lambda Cloud to dedicated GPU servers for continuous processing, lower per-item costs, and elimination…
Migrate from Together.ai to Dedicated GPU: Batch Processing
Move your batch LLM processing from Together.ai's API to dedicated GPUs for dramatically lower per-item costs and no rate limit…
Migrate from Together.ai to Dedicated GPU: Model Evaluation
Run comprehensive model evaluations on dedicated GPU hardware instead of Together.ai for unlimited benchmark throughput, custom evaluation suites, and reproducible…
Migrate from Together.ai to Dedicated GPU: RAG Pipeline
Self-host your RAG pipeline on dedicated GPUs instead of Together.ai for lower latency, zero per-query token costs, and full control…
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 ServersPyTorch Hosting
GPU-accelerated PyTorch on dedicated servers — CUDA, cuDNN, and NVMe pre-configured.
Deploy PyTorchvLLM Hosting
High-throughput LLM serving with vLLM — deploy on dedicated GPU hardware.
Deploy vLLMOllama Hosting
Run open source LLMs with Ollama — the simplest path to self-hosted AI.
Deploy OllamaOpen 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.
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