Getting-Started Guides
10 InsiderLLM guides in Getting-Started — practical, tested walkthroughs for running AI locally, sorted by most recently updated.
- Qwen 3.5 Locally — 27B vs 35B-A3B vs 122B, Which Model Fits Your GPU Qwen 3.5 and 3.6 on local hardware. 27B dense vs 35B-A3B MoE vs 122B compared. VRAM tables, community tok/s on RTX 3090, and which to pick for your card.
- Ollama Troubleshooting Guide: Every Common Problem and Fix GPU not detected? Running at 1/30th speed on CPU? OOM crashes mid-generation? Every common Ollama error with exact diagnostic commands and fixes for Mac, Windows, and Linux. Updated July 2026 for v0.31.x and Qwen 3.5 + 3.6.
- Open WebUI Setup Guide: ChatGPT UI for Local AI 1 Docker command gives you a ChatGPT-like interface for any Ollama model. 120K+ GitHub stars, built-in RAG, voice chat, and multi-model switching—all running locally.
- Ollama 0.30.0: What's New, What's Faster, What Breaks on Upgrade Ollama 0.30.0: llama.cpp integration, flash-attention default for Qwen/Gemma, broader model support. Firsthand upgrade notes, known issues to watch.
- Run Your First Local LLM in 15 Minutes Install Ollama, pull a model, and chat with AI offline—all in 15 minutes. Works on any Mac, Windows, or Linux machine with 8GB RAM. No accounts, no API keys, no fees.
- Ollama vs LM Studio: Speed, Setup, and Verdict Ollama gives you a CLI with 100+ models and an OpenAI-compatible API. LM Studio gives you a visual GUI with one-click downloads. Most power users run both—here's when to use each.
- The AI Market Panic Explained: Why Running Local Models Puts You on the Right Side of the Gap A speculative fiction piece crashed stocks $100B+ in a day. IBM dropped 13%. The real story isn't the doom — it's the capability-dissipation gap, and where you sit on it.
- Ubuntu 26.04 Is Built for Local AI — What Actually Changes Ubuntu 26.04 LTS packages NVIDIA CUDA and AMD ROCm in official repos. No more external downloads or dependency nightmares. What's confirmed and what it means for local AI.
- LiquidAI LFM2: The First Hybrid Model Built for Your Hardware LFM2-24B-A2B runs at 112 tok/s on CPU with only 2.3B active params. Not a transformer. GGUF files from 13.5GB, Ollama and llama.cpp setup, and where it beats Qwen.
- The Local AI Complexity Cliff: Why the Jump from Hello World to Useful Is So Hard Getting Ollama running takes 5 minutes. Building something useful takes weeks of hitting walls you didn't know existed. Here's an honest map of every stage, with time estimates and what unlocks at each level.
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