GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Rolling Model Upgrade on an Inference Server
Replace replicas one at a time with the new model version. Cheaper than blue-green when you have multiple GPUs in one chassis.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Hybrid Search – BM25 Plus Embeddings on a GPU Server
Hybrid search combines classical lexical matching with dense vector retrieval. The implementation pattern that actually works in production.
Caddy Reverse Proxy for Ollama Setup
Caddy automates TLS and has a dead-simple config format. For a small Ollama deployment, it is a lower-friction alternative to…
RTX 5060 Ti 16GB for NLLB-200: 200-Language Translation Hosting
Meta's NLLB-200-3.3B runs at 350 tokens/s on the RTX 5060 Ti 16GB with 7 GB FP16 footprint, covering 200 languages…
Self-Host JupyterHub on a Dedicated GPU
JupyterHub gives every team member their own Jupyter notebook on a shared GPU server. The right setup for data science…
SDXL Lightning vs Turbo – Benchmark Comparison
Both variants generate SDXL images in 1-4 steps instead of 30. Quality and speed differ enough to justify picking carefully.
SaaS Unit Economics When LLM Is a Cost Center
LLM inference is expensive enough that it changes SaaS unit economics materially. Modelling cost per user and gross margin honestly.
IP-Adapter Production Setup
IP-Adapter conditions diffusion generation on reference images rather than text. Essential for style transfer and product placement pipelines.
InstantID Pipeline on a GPU Server
InstantID preserves facial identity across generated images from a single reference photo. Self-hosted with SDXL it becomes a reliable portrait…
ICO Guidance on Self-Hosted AI in the UK
The Information Commissioner's Office has issued specific guidance on AI and personal data. A practical summary for UK businesses on…
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