#Mobile

Cactus Compute shipped Needle 2: 45M parameters, a 14 MB binary, a session in 28 MB of RAM, 500 tokens/s on a Raspberry Pi 5 and 70 MFLOPs per token versus 460 for LFM2.5 230M. The engineering is real: CQ2-bit quantization applied from pre-training onward, a byte-level grammar that locks the output to valid function calls. But the Show HN turned into a public failure lab: typing "HN" fires lock_door with confidence 0, "warmer" becomes mode cool, and the ESP32 demo that went viral was Needle 1.