Key Points

IBM released the Granite 4.1 family of Apache-2.0 LLMs in multiple sizes (3B, 8B, and 30B) and published detailed information on how the models are built.
Unsloth published 21 GGUF quantized variants of the Granite 4.1 3B model, totaling 51.3GB of model files ranging from about 1.2GB to 6.34GB.
The author ran an experiment prompting different quantized variants to generate an SVG of “a pelican riding a bicycle,” comparing how output quality changed with model size.
The results were surprisingly inconsistent, with no clear quality-versus-size pattern; the smallest model produced the best-looking bicycle, while the largest was only slightly more pelican-like.
The author plans to repeat the experiment later using a model better suited for drawing pelicans, suggesting the exercise is as much about model capability as quantization size.

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Granite 4.1 3B SVG Pelican Gallery. IBM released their Granite 4.1 family of LLMs a few days ago. They're Apache 2.0 licensed and come in 3B, 8B and 30B sizes.

Granite 4.1 LLMs: How They’re Built by Granite team member Yousaf Shah describes the training process in detail.

Unsloth released the unsloth/granite-4.1-3b-GGUF collection of GGUF encoded quantized variants of the 3B model - 21 different model files ranging in size from 1.2GB to 6.34GB.

All 21 of those Unsloth files add up to 51.3GB, which inspired me to finally try an experiment I've been wanting to run for ages: prompting "Generate an SVG of a pelican riding a bicycle" against different sized quantized variants of the same model to see what the results would look like.

Honestly, the results are less interesting than I expected. There's no distinguishable pattern relating quality to size - they're all pretty terrible!

Six different SVG images from models ranging in size from 1.67GB to 1.2GB. They are almost all an abstract collection of shapes - weirdly the smallest model had the best version of a bicycle, while the largest one had something that looked a tiny bit like a pelican.