C3G is a novel feed-forward framework that efficiently reconstructs and understands 3D scenes from sparse multi-view images by estimating a compact set of 2,048 3D Gaussians. This approach significantly reduces memory overhead and improves multi-view feature aggregation compared to dense, per-pixel methods, leading to superior performance in novel view synthesis and 3D open-vocabulary segmentation.