#localinference

Running a 70B parameter model to summarize a 200-word email is wasteful. Running a 3B model to review...

LLM costs scale linearly with usage. A system processing 10,000 requests a day at $0.01 per request...

A practical guide to local AI hardware in 2026, covering old laptops, Mac mini, Mac Studio, NVIDIA DGX Spark, DIY GPU boxes, and which classes of models each device can realistically run well.

A practical guide to local AI hardware in 2026, covering old laptops, Mac mini, Mac Studio, NVIDIA DGX Spark, DIY GPU boxes, and which classes of models each device can realistically run well.

NVIDIA dropped Nemotron 3 Super at GTC last week and the spec sheet looks like a typo. 120 billion total parameters. 12 billion active at inference ti

Comparing cloud AI inference vs the tinybox for on-prem offline workloads — cost analysis, privacy tradeoffs, and when local hardware actually makes sense.

Ollama 0.19 ships with an MLX backend preview that nearly doubles decode speed on Apple Silicon. Step-by-step guide to enabling it, benchmarking before and after, hardware requirements, and an honest look at what works and what doesn't yet.

Imagine running LLMs and GenAI models with a single Docker command — locally, seamlessly, and...