Run AI models on your own laptop, GPU or server: setup guides, hardware, benchmarks and when local beats the cloud.
Most read by people in Engineering, IT and Legal & Compliance.
Run Spark-X2.6-4B, an Apache 2.0 4B on-device agent model with 1M-token context, via Ollama, llama.cpp, LM Studio, MLX, vLLM or SGLang.
Run NVIDIA Dory1.0-4B locally with vLLM or llama.cpp on Apple Silicon, choose 1, 2 or 4 loops, and cut KV cache memory with last-loop caching.
DeepSeek-V4.1-Flash-1017 ships MIT-licensed with no Jinja template. See sampling settings, 1M context, the encoding folder and deepseek-recipe.
NVIDIA's open-weight Nemotron 3.5 Super VL uses Mamba-2, MoE and attention with 120B total, 12B active parameters and 1M context. Here is where it fits.
Enable developer mode on an LG or Android TV, find its IP, and point Hermes agent at a local Qwen model in Ollama to manage settings with an undo list.
Hands-on results for NVIDIA's open Nemotron 3.5 Super VL (120B, 12B active): bug fixing, vision, translation, circuits, and benchmarks.
Ornith-1.5-122B tested on a Docker bug fix, vision, screenshot reasoning, creative HTML and 80-language translation. Here is where it held up and failed.
Learn how to run local AI models with Ollama or LM Studio on a laptop, GPU, or phone, plus local image and music generation and API cost break-even.
Learn how to run CUDA apps on AMD GPUs with ZLUDA on Windows: setup steps, supported GPUs, legal risk under NVIDIA's EULA, and what still breaks.
Build a local AI coding agent on an M4 Mac Mini with Ollama's MLX backend, Qwen3-Coder-Next, Serena MCP tools, and a Panel chat UI. No token billing.
An agentic OS lets AI agents act on files, settings, and apps. See how Windows 11 and Omarchy Linux differ on who controls the agent, plus real risks.
Learn how to run Claude Code, Codex, or Cline locally with Magnitude in three steps, plus DeepSeek vs OpenAI cost math and the tool's alpha limits.
Learn how to pick, quantize, and run distilled models like DeepSeek-R1 locally with Ollama or llama.cpp, and when self-hosting beats API costs.
Omarchy is DHH's Arch and Hyprland desktop with built-in AI coding agents. See review scores, security issues, costs vs Codespaces, and who should switch.
Compare Ollama, LM Studio, llama.cpp, Open WebUI, AnythingLLM, and vLLM across runtime, interface, and server layers, plus VRAM needs and cost.
Compare Llama, Qwen, Mistral, DeepSeek, gpt-oss, and small models by license, hardware needs, and self-hosting break-even to pick one for internal tools.
Build a local AI second brain with markdown notes, Ollama, a local vector store for RAG, and automation. Covers hardware needs, tradeoffs, and maintenance.
Learn how to run 671B MoE models like DeepSeek R1 locally with llama.cpp, KTransformers and Unsloth quants, with hardware tiers and tokens per second.
Learn how to run a local LLM for business: hardware tiers, 7B-30B model picks, Ollama and vLLM setup, and when owning GPUs beats paying API bills.
Learn what an LLM proxy is and how to set one up with LiteLLM to log prompts, tool calls, and spend from local AI agents like Ollama, Cline, and Continue.
DHS banned DeepSeek from 100+ federal agencies. See what running AI models locally costs, from a $6,000 CPU build to H100 clusters, and when it beats APIs.
Court orders, training opt-outs, and leaks at OpenAI, Anthropic, and xAI show renting AI exposes your data. Here's the case for running open weights yourself.
Omarchy ships 10 AI coding agents built into the desktop. A hands-on look at what works, what's shaky, and who should actually run it.
Enterprises spend $12.5B a year renting frontier AI APIs. Here's the distillation pipeline that turns that spend into owned models, 75-98% cheaper to run.