subcluster
Endpoint Types
12 articles
Articles
August 14, 2026
How to use Lyceum API within Claude Code
European AI consultancies need a GDPR-compliant way to use Claude Code. By routing it through an API wrapper, you can point the tool to Lyceum's OpenAI-compatible Dedicated Inference endpoint and use sovereign, open-weight models for sensitive client coding tasks.
June 6, 2026
Streaming Inference API: Architecting Real-Time AI Agents
Real-time AI agents require sub-second Time-to-First-Token (TTFT) to function naturally. But achieving this on hyperscaler infrastructure often leads to cost overruns, OOM errors, and compliance risks.
May 28, 2026
Deploy a Hugging Face Model Inference API: 2026 Production Guide
Moving a Hugging Face model from a local notebook to a production API requires solving three hard problems: GPU memory fragmentation, unpredictable cold starts, and strict data residency requirements.
May 24, 2026
Deploy Hugging Face Model to GPU Cloud
Moving a Hugging Face model from a local notebook to production requires strict VRAM math and the right inference engine. Learn how to deploy open-source LLMs at scale without hyperscaler cost overruns.
April 22, 2026
Self-Host LLM APIs on EU Infrastructure: The Modern Guide
As hyperscaler credits expire and the EU AI Act's high-risk obligations phase in, deferred to 2 December 2027 for Annex III systems and 2 August 2028 for Annex I systems, AI teams are moving toward sovereign infrastructure. This guide explores how to self-host LLM APIs in Europe to ensure data residency without sacrificing performance.
April 22, 2026
Serverless GPU Inference: Architecture, Economics, and Compliance
Most AI infrastructure leads struggle with low GPU utilization, which erodes margin. Serverless GPU inference offers a path to eliminate idle capacity while maintaining the low-latency performance required for production LLMs.
April 18, 2026
Host Fine-Tuned Model Production APIs: A Technical Guide
Moving a fine-tuned model from a local notebook to a production API requires solving for memory management, cold starts, and unsustainable hyperscaler costs. This guide explores the technical architecture needed to serve LLMs with high throughput while keeping processing inside European data centers.
April 17, 2026
Deploying Mistral Large on European GPU Cloud Infrastructure
European AI teams face a dilemma: high-performance LLMs like Mistral Large 2 require massive GPU clusters, but US-based clouds often fail strict GDPR and data residency requirements. This guide explores how to deploy Mistral Large 2 on EU-sovereign infrastructure without the hyperscaler price tag.
April 17, 2026
Deploying Private LLM Endpoints on GPU Cloud: A 2026 Strategy
As AI startups outgrow their initial cloud credits, the shift toward private LLM endpoints becomes a necessity for cost control and GDPR compliance. This guide examines the technical architecture and economic frameworks required to deploy high-performance inference on European GPU infrastructure.
April 16, 2026
Deploying Custom Docker Model Inference APIs for Production
Moving beyond black-box APIs requires a robust containerization strategy and optimized GPU orchestration. This guide explores how to build and deploy custom Docker inference endpoints that maintain data residency while maximizing throughput.
April 16, 2026
Deploying Llama 3 Inference APIs on Sovereign GPU Clouds
Scaling Llama 3 inference requires balancing VRAM bottlenecks against unsustainable hyperscaler costs. This guide explores how to deploy production-grade APIs using European infrastructure and modern orchestration stacks.
April 15, 2026
Dedicated vs Shared GPU Inference: Scaling AI Infrastructure
Choosing between dedicated and shared GPU resources is no longer only a cost calculation. The decision hinges on latency consistency, memory bandwidth isolation, and the strict requirements of the EU AI Act.