Maincoder-1B: 76% HumanEval in 1B Parameters
Maincoder-1B achieves 76% on HumanEval with just 1 billion parameters, demonstrating exceptional code generation efficiency in a compact model architecture.
Someone stumbled on Maincoder-1B, a tiny 1B-parameter coding model that punches way above its weight class. It hits 76% on HumanEval, which is pretty impressive for something this small.
The interesting bit - it’s designed to run locally on modest hardware instead of requiring cloud GPUs. Fits nicely for batch refactoring jobs, offline coding tools, or anything needing lots of cheap generations.
Get it here: https://huggingface.co/Maincode/Maincoder-1B
Released under Apache 2.0, so no licensing headaches. Trade-off is a ~2k context window, so it works best for small, focused tasks rather than navigating huge codebases.
Good option if waiting 10 seconds for a cloud model to generate boilerplate code gets old, or for running hundreds of generations in search/verification loops without burning through API credits.
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