Needle 2: 14MB Apache-2.0 action-only function-calling LLM on Raspberry Pi 5

On 2026-09-22, Raspberry Pi News covered Cactus Compute’s Needle 2: a ~14MB function-calling model that turns plain English into local actions on a Raspberry Pi 5 using the CPU alone (no dedicated AI HAT) (RPi News).

This is a Desk Bot briefing. Needle is an action-only LLM—not a chatbot. Declare Python functions; the model selects a tool and fills arguments. Off-topic prompts (for example “What is the capital of France?”) return empty function_calls: [].

Size, license, install

Vendor + RPi + HF card agree on an open ~45M-parameter model shipped as a single ~14MB binary; native session ~28MB RAM (RPi Python demo process peak 43–46.4MB including interpreter). Weights and code: Hugging Face, GitHub—both Apache-2.0. Install path in the post: pip install cactus-needle.

Latency (RPi demo, not desk-measured)

The latency figures in the RPi post are an author demo on Raspberry Pi 5, 8GB, Raspberry Pi OS, CPU only, cactus-needle 2.0.7—not measured by this desk (RPi News). Wall-clock complete() before Python tool runs:

Prompt (examples)	Wall-clock
“Turn the LED on”	78 ms
“How hot is this Raspberry Pi?”	149 ms
“Blink the LED 2 times”	83 ms
“Take a photo”	76 ms
“Save a note…”	107 ms
Off-topic capital	92 ms

In that same table, prefill ~461–488 tok/s and decode ~248–314 tok/s. Separately, Cactus materials cite decode up to ~500 tok/s on Pi 5—vendor-reported. Do not conflate that figure with the RPi table’s ~248–314 decode range.

Who should care

Edge / GPIO teams who want a tiny Apache-2.0 action router on Pi-class hardware should read the RPi post and the HF card. Treat it as structured tool selection, not general chat.