Topic
AI & LLMs
Models you can run on your own hardware, prompt patterns that ship, agent frameworks that don't catch fire, and the awkward questions nobody answers in the breathless launch posts. Ollama, vLLM, llama.cpp, LocalAI, plus the quieter stuff — embeddings, RAG, evals, and figuring out when the cloud API is actually the right answer. If you'd rather understand the trade-offs than chase benchmarks, you'll feel at home here.
80 articles in this topic.
Featured posts
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Local Coding Agents Need Less Context
Local coding agents don't fail because your 27B model is too small. They fail because you let 200K tokens of garbage pile up in the context window. Cap it low.
15 min read -
LM Studio vs Jan vs GPT4All: Desktop LLM Clients
LM Studio, Jan, and GPT4All compared, the best desktop LLM clients for local AI chat on Mac, Windows, and Linux in 2026.
10 min read -
RAGAS: Evaluating RAG Without Vibes
Stop guessing if your RAG pipeline works. RAGAS gives you reproducible metrics: faithfulness, answer relevance, context precision and recall.
9 min read -
KV Cache Quantization: Free LLM Context, Almost
KV cache eats your VRAM at long context, not the weights. Q8/Q4 KV quantization in llama.cpp and vLLM cuts it 2-4x with almost no quality hit.
9 min read -
Aider & Cline: Terminal AI Coding That Actually Ships
Aider vs Cline: two agentic AI coding tools that go beyond autocomplete. Which terminal AI coding agent ships cleaner work?
9 min read -
Mixture of Experts (MoE) for Self-Hosters, Demystified
MoE LLMs like Mixtral and DeepSeek-V3 run 70B-class quality on 7B-ish active params. Here's how sparse activation works and how to run it at home.
10 min read
All AI & LLMs articles
- Local Coding Agents Need Less Context
- LM Studio vs Jan vs GPT4All: Desktop LLM Clients
- RAGAS: Evaluating RAG Without Vibes
- KV Cache Quantization: Free LLM Context, Almost
- Aider & Cline: Terminal AI Coding That Actually Ships
- Mixture of Experts (MoE) for Self-Hosters, Demystified
- Python Libraries Worth Your Time in 2026
- Speculative Decoding: Faster LLMs With a Tiny Sidekick
- Karakeep: Self-Hosted Bookmarks With AI Tagging
- Stop Feeding the AI Your Whole Repo
- RTK vs snip vs lean-ctx: Token Killers
- Hailo-8 vs Coral: AI Accelerators for the Edge
- AI Swarm Audited My 840-Post Blog
- Used GPU Buying Guide for Home Lab LLMs
- Claude Code in a Homelab Workflow
- Self-Host a Local AI Coding Workhorse
- Give Your AI Agent a Cheap Intern
- Claude Code + SearXNG: Private Web Search
- Dify: Visual Agent Workflows
- CUDA vs ROCm vs CPU: Running AI on Whatever GPU You've Got
- Exploring the Diverse World of LLM Models
- Key Parameters of Large Language Models
- LangGraph vs CrewAI vs AutoGen: AI Agent Frameworks for Mere Mortals
- Large Language Model Formats and Quantization
- LiteLLM & vLLM: One API to Rule All Your Models
- Local Vision LLMs Worth Running in 2026
- Ollama Beyond the Basics: Model Management, Custom Models, and Optimization
- Ollama Memory Management: Why Models Keep Loading
- Open WebUI vs LibreChat: Self-Hosted ChatGPT Alternatives Compared
- Piper vs Coqui: Text-to-Speech on Your Own Hardware (Because AWS Polly Charges Per Character Like It's 1999 SMS)
- Prompt Engineering for Generative AI 101
- Stable Diffusion vs ComfyUI vs Fooocus: AI Image Generation at Home
- Text Generation Web UI vs KoboldCpp: Power User LLM Interfaces
- OpenRouter vs LiteLLM
- Function Calling in Local LLMs
- Gemma 4 vs Qwen3.6
- AnythingLLM as Knowledge Base
- MCP Servers: Tools for LLMs
- RAG Evaluation with Ragas
- LLM Distillation Explained
- Open WebUI Tools, Functions & Pipelines: Extend Your Local LLM
- Self-Supervised Learning Explained
- Ollama Model Management: Beyond ollama run
- Continue.dev vs Cody vs Tabby: AI Code Help Without the Cloud
- LangGraph vs CrewAI vs AutoGen: AI Agents Without the Hype
- n8n + LLM: Building Automations That Actually Think
- Qdrant vs Weaviate vs Chroma: Vector DB Showdown
- CUDA vs ROCm vs CPU: Running AI on Whatever GPU You've Got
- LangGraph vs CrewAI vs AutoGen: AI Agent Frameworks for Mere Mortals
- Whisper & Faster-Whisper: Self-Hosted Speech-to-Text That Actually Works
- LiteLLM & vLLM: One API to Rule All Your Models
- RAG on a Budget: Building a Knowledge Base with Ollama & ChromaDB
- LangChain vs LlamaIndex: RAG Framework Showdown
- The Embedding Model Choice Nobody Explains
- GPU Memory Math: Will This Model Actually Fit?
- Beyond RAG: When a Virtual Filesystem Works Better
- Running Gemma 4 Locally with Ollama
- 1-Bit LLMs: The Quantization Endgame
- AMD Lemonade: Local LLM Serving for AMD GPUs
- When to Use Structured Output (JSON Mode) in LLMs
- Using AI to Find Security Bugs in Your Code
- LLM Temperature and top_p Explained Without the Math
- LLM Backends: vLLM vs llama.cpp vs Ollama
- RAG Chunking: Why Chunk Size Is Everything
- System Prompts: The LLM Feature Most People Ignore
- LLM Quantization: Q4_K_M Isn't Always the Best Choice
- Running Multiple Ollama Models Without Running Out of RAM
- Context Window vs Token Limit: Not the Same Thing
- RAG on a Budget: Building a Knowledge Base with Ollama & ChromaDB
- Stable Diffusion vs ComfyUI vs Fooocus: AI Image Generation at Home
- n8n + LLM: Building Automations That Actually Think
- LLM Fine-Tuning for Mortals: LoRA, QLoRA, and Your Gaming GPU
- Whisper & Faster-Whisper: Self-Hosted Speech-to-Text That Actually Works
- Continue.dev vs Cody vs Tabby: AI Code Assists That Live on Your Machine
- Flowise vs Langflow: Build AI Pipelines Without Writing a Novel
- n8n vs Node-RED: Automate Everything Without Learning to Code (Much)
- Prompts for Image Generation in Stable Diffusion
- Ollama: Powerful Language Models on Your Own Machine
- Unleash the Power of LLMs with LocalAI
- Machine Learning models (AI)