Tag: llm

Replace Perplexity with SearXNG + a local LLM for private, cited web search. Full Perplexica/Morphic deploy walkthrough, Ollama, latency tradeoffs.

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.

LM Studio, Jan, and GPT4All compared, the best desktop LLM clients for local AI chat on Mac, Windows, and Linux in 2026.

Stop guessing if your RAG pipeline works. RAGAS gives you reproducible metrics: faithfulness, answer relevance, context precision and recall.

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.

Aider vs Cline: two agentic AI coding tools that go beyond autocomplete. Which terminal AI coding agent ships cleaner work?

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.

Speculative decoding, Gemma 4 MTP, and DeepSeek DSpark all make LLMs 2-6x faster losslessly. How each works, and which to use for local vs. serving.

Karakeep (formerly Hoarder) is a self-hosted Pocket alternative with AI auto-tagging, full-text search, and Docker Compose deploy in under 10 minutes.

Comparing context-mode, code-review-graph, token-savior, and claude-context, MCP tools that stop AI coding agents from reading your whole codebase blind.

RTK, snip, and lean-ctx filter your AI coding agent's output before it burns context tokens. I run RTK daily, here's the one I'd actually switch to.

I pointed a parallel swarm of AI agents at 840 technical posts to fact-check and refresh them, the architecture, the token bill, and the guardrails.