Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Add AI capabilities to your Supabase backend using a self-hosted LLM on GPU. This guide covers Edge Functions that call your inference endpoint, database triggers for AI processing, and building…
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Deploy a Vercel frontend that calls your own GPU-hosted AI backend. This guide covers the Vercel AI SDK, API route…
Test and debug your GPU-hosted AI API using Postman. This guide covers creating a Postman collection for your self-hosted LLM…
Run Jupyter Notebook directly on your GPU server for interactive AI development. This guide covers remote Jupyter setup, SSH tunnelling,…
Wire Microsoft Teams to a self-hosted AI model on your own GPU server. This tutorial covers the Bot Framework setup,…
Connect IntelliJ, PyCharm, or WebStorm to a self-hosted AI model on GPU for private code completion and chat. This guide…
Stream AI responses from your GPU server into a Flutter application. This guide covers building a streaming HTTP client in…
Stream AI responses from your GPU server into a Vue.js application. This guide covers building a composable for streaming chat…
Stream AI responses from your GPU server into a Next.js application using server-side API routes. This guide covers building a…
Stream AI responses from your GPU server directly into a React application. This guide covers fetching completions from your self-hosted…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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