Neura saysLocal inference (Ollama, llama.cpp, LM Studio) runs open models on your own machine.
You don't always need the cloud. llama.cpp runs quantized models efficiently on CPUs/consumer GPUs; Ollama wraps it with a simple "pull and run" CLI/API; LM Studio gives a GUI. Benefits: privacy (data never leaves), no per-token cost, offline use. Limits: you're capped by your hardware and the smaller/quantized models that fit. Great for development, privacy, and tinkering.
Power-ups you unlock
Run open models locally (no cloud)
llama.cpp · Ollama · LM Studio
Private, free per-token, offline
Limited by your hardware/model size
The Overfit Ogre attacks — common mistakes
Expecting frontier quality from a laptop model
Ignoring quantization quality trade-offs
Underestimating RAM/VRAM requirements
Boss battleList two reasons to run a model locally instead of via API.
Example code
<!doctype html><html><head><meta charset="utf-8"></head>
<body style="background:#06040d;color:#e6e0ff;font-family:monospace;padding:20px"><pre>ollama run llama3 # pull + run locally
private · offline · no per-token cost
capped by your hardware</pre></body></html>