finally some progress on running stuff locally without needing a massive gpu. seeing models that are only 8 to 29mb and claiming they can match deepseek v4 flash sounds almost too good to be true. the whole
intelligence laddering thing seems interesting if it actually works for complex tasks though. i'm looking at how they use regex triggers to force tool calls when confidence is low. it's a bit of a hack, but might save us from those annoying misrouted requests. the python setup looks dead simple since you just decorate your functions and let
needle handle the rest.
import needledef get_weather(city: str): "Get the current weather for a city." return {"city": city, "temp_c": 27}it's basically just reading docstrings to figure out what to do. i'm skeptical about how much it'll struggle once you add more than a handful of tools. the regex logic for avoiding collisions looks like a headache to maintain if the toolset grows. anyone tried running these tiny binaries on actual edge hardware yet?
full read:
https://cactuscompute.com/needle