4 articles matching your search.
A hands-on comparison of the four small language models I tested in production builds during 2026 — benchmarks, memory footprints, licensing traps, and what broke on real phones.
Ollama switched to Apple MLX framework and my M2 MacBook Air went from 14 to 47 tokens per second. Full benchmarks, setup guide, and what this means for local AI.
CERN uses tiny AI models compiled directly into FPGA silicon to filter LHC collision data in under 50 nanoseconds. Here is why their approach matters for enterprise edge AI.
A developer ran a 400 billion parameter AI model on an iPhone 17 Pro at 0.6 tokens per second. The headline is impressive but the real story is more nuanced.