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.
Ollama on a 4060 8GB — what fits at GGUF Q4. Hobby tier only.
Reranker architecture choice — cross-encoder accuracy vs bi-encoder speed. The 2026 production default.
The first-week roadmap for committing to self-hosted AI — what to set up first, what to defer, what to skip.
Tokenizer choice and tokens-per-language differences. Why your French content costs more than English.
Distilling long retrieved context into shorter focused context before final LLM call. The pattern that improves quality + cost.
For long-running agent tasks, async execution with status updates beats synchronous. The pattern.
Metering AI usage for SaaS billing — tokens, requests, storage, fine-tunes. The implementation that holds up to audit.
Designing the feedback collection mechanism for production AI — UX, infrastructure, what to do with the data.
How agentic AI workloads manage state across multi-step interactions — conversation, tool results, working memory.
When tool calls fail mid-agent-loop — recovery patterns, retry semantics, fallback strategies.
From the blog to your next deployment — pick the right platform for your workload.
Bare-metal servers with a dedicated GPU, NVMe, full root access, and 1Gbps networking from our UK datacenter.
Browse GPU ServersGPU-accelerated PyTorch on dedicated servers — CUDA, cuDNN, and NVMe pre-configured.
Deploy PyTorchHigh-throughput LLM serving with vLLM — deploy on dedicated GPU hardware.
Deploy vLLMRun open source LLMs with Ollama — the simplest path to self-hosted AI.
Deploy OllamaDeploy LLaMA, Mistral, DeepSeek, and more on dedicated hardware with no per-token API fees.
Explore LLM HostingReal-world tokens per second data across every GPU we offer, tested on popular LLMs.
View BenchmarksDedicated GPU servers from our UK datacenter. NVMe storage, 1Gbps networking, full root access.