A hardware-focused tutorial on building a dedicated AI inference server using consumer components. Focus on the sweet spot of dual used RTX 3090s or a single RTX 4090. Key Sections: 1. **Component Selection:** Why VRAM is king. The concept of ‘VRAM per dollar’. 2. **The Build:** Physical assembly notes, cooling requirements for continuous load. 3. […]
The $1,500 Local AI Server: DeepSeek-R1 on Consumer Hardware Read More »
A comparative guide for developers seeking a private, free alternative to GitHub Copilot. Contrasts the polished experience of Cursor with the DIY flexibility of VS Code + Continue. Key Sections: 1. **The Privacy Imperative:** Why send code to the cloud if you don’t have to? 2. **Setup Guide:** Configuring Ollama with DeepSeek-Coder-V2. 3. **Integration:** Setting
Local AI Coding Assistant: Cursor vs VS Code + Ollama + Continue Read More »
A technical migration guide for teams outgrowing Ollama’s developer-friendly experience and needing vLLM’s production throughput. Key Sections: 1. **When to Migrate:** Identifying bottlenecks (concurrency, latency spikes). 2. **Architecture Comparison:** Ollama’s monolithic approach vs vLLM’s PagedAttention and decoupled architecture. 3. **Migration Steps:** Converting Modelfiles to Docker-compose setups, handling quantization format changes (GGUF to AWQ/GPTQ). 4. **API
Ollama vs vLLM: A Migration Guide for Scaling Teams Read More »
A comprehensive pillar guide on architecting, deploying, and managing local Large Language Models (LLMs) for enterprise and production use cases in 2026. This article must move beyond ‘how to install Ollama’ and cover the full stack: hardware selection (H100 vs A100 vs RTX 4090 clusters), inference engine selection (vLLM vs TGI vs TensorRT-LLM), and observability
The 2026 Definitive Guide to Running Local LLMs in Production Read More »
Build your own private Copilot alternative that runs entirely locally. Zero subscription fees, complete privacy, and surprisingly good code completion. Continue reading Local AI Coding Assistant: Complete VS Code + Ollama + Continue Setup on SitePoint.
Local AI Coding Assistant: Complete VS Code + Ollama + Continue Setup Read More »
Ollama is perfect for local development, but when your team grows past 3 concurrent users, performance drops dramatically. This guide shows you exactly when to migrate to vLLM and how to do it without downtime. Continue reading From Ollama to vLLM: A Migration Guide for Growing Teams on SitePoint.
From Ollama to vLLM: A Migration Guide for Growing Teams Read More »
Compare the top local LLM models for developers in 2026. Includes benchmark performance, use cases, and recommendations for different hardware setups. Continue reading Best Local LLM Models for Developers in 2026 on SitePoint.
Best Local LLM Models for Developers in 2026 Read More »
A comprehensive guide to running local large language models in 2026. Learn about Ollama, LM Studio, and other tools for privacy-focused AI development on your own hardware. Continue reading How to Run Local LLMs in 2026: The Complete Developer’s Guide on SitePoint.
How to Run Local LLMs in 2026: The Complete Developer’s Guide Read More »
Master Ollama in 2026 with this professional setup guide. Configure models, optimize performance, and integrate with your development workflow. Continue reading Ollama Setup Guide: Run Local LLMs Like a Pro in 2026 on SitePoint.
Ollama Setup Guide: Run Local LLMs Like a Pro in 2026 Read More »
Understanding model quantization is crucial for running LLMs locally. We break down the math, trade-offs, and help you choose the right format for your hardware. Continue reading Quantization Explained: Q4_K_M vs AWQ vs FP16 for Local LLMs on SitePoint.
Quantization Explained: Q4_K_M vs AWQ vs FP16 for Local LLMs Read More »
