Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
How self-hosted AI cost has evolved 2023-2026 and where it's heading. The trajectory matters for capacity planning.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
April 2026 snapshot of standard LLM benchmark leaders. The reference for picking models by task.
Reranker architecture choice — cross-encoder accuracy vs bi-encoder speed. The 2026 production default.
Should your AI API be GraphQL or REST / OpenAI-compatible? The trade-offs and the production default.
Where CDN caching helps for AI — and where it doesn't. The patterns that work for streaming and structured outputs.
Evaluating ML / AI platforms (Databricks, SageMaker, Vertex, Foundry) — the criteria that matter beyond marketing.
AWS Comprehend offers managed NLP (sentiment, entities, classification). Self-hosted small LLMs cover the same tasks at a fraction of cost.
Ollama on a 4060 8GB — what fits at GGUF Q4. Hobby tier only.
How frontend apps consume SSE streams from LLMs — React hooks, optimistic UI, abort handling.
Orchestrating multiple specialised agents on a shared task — supervisor, peer-collaboration, role-based patterns.
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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