TinyStories is a useful experiment because its language task is simple enough to evaluate while still exposing the practical limits of memory, runtime and token generation speed.
What you need
Use a Raspberry Pi 5 with current system software, reliable power and enough storage for the runtime and model files. A heatsink or active cooling helps maintain stable performance during repeated runs.
A five-step workflow
- update the operating system and install the compiler and runtime dependencies;
- build or install a CPU-oriented inference runtime;
- obtain a compact TinyStories-compatible model;
- run a fixed prompt and record time to first token and generation speed;
- repeat the measurement after changing one parameter at a time.
What the experiment teaches
Small hardware forces useful engineering discipline. Memory use, quantisation, prompt length and thermal behaviour all become visible. That makes the Pi a strong testbed for edge inference, even when the final deployment uses different hardware.