Little Learner: 900MB models that learn on the kid's tablet

A new paper from researchers at Baidu, Oxford, and others introduces Little Learner, a tiny LLM that weighs in at roughly 900MB — small enough to run on a low-end tablet or even a Raspberry Pi without an internet connection. The model is built on a 1.6 billion parameter architecture, pruned and quantized to fit in flash storage, and trained from scratch rather than distilled from a bigger model. That matters: distilled models carry the biases and blind spots of their parent, while this one learns its own patterns.

The team reports competitive results on MMLU and GSM8K — standard benchmarks for reasoning and knowledge — despite the size. The real test is deployment: running inference locally means no API bills, no latency spikes from a server farm, and no privacy leak when a kid types a question into a device they already own. For families and schools operating on thin budgets, this is the kind of thing that lets you put a capable model on a tablet and walk away.

Why this matters for us: los primos que estudian en casa con un iPad viejo no necesitan la nube — este modelo se lleva en la mochila.