Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Production checklist for self-hosted LLM deployments — security, observability, eval, scaling, compliance. The reference list.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
If you're cutting AI costs in 2026, here are the highest-ROI levers — from per-token economics to right-sized hardware to…
What does a complete small-team AI stack look like in 2026? Hardware, software, ops — the canonical blueprint.
Three patterns for production AI: self-hosted dedicated, managed inference (Together AI / Fireworks / Replicate), hosted frontier API. The decision…
Internal AI tooling — engineering productivity, ops automation, internal Q&A — fits cleanly on a single 4090. Sizing and stack.
Where self-hosted AI sits in April 2026 — the maturity, the picks, the patterns.
The 2026 self-hosted AI summary — the picks, the patterns, the trade-offs.
What does it cost to embed a million documents on a dedicated GPU?
A step-by-step LoRA fine-tune on Llama 3 8B with Unsloth, PEFT and TRL - config, code and wall-clock times.
The classic mid-tier to flagship step - 16GB Blackwell to 32GB Blackwell. What you gain and when it pays back.
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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