Part 3/10:
One of the most striking aspects of V3.1 is its exceptional performance scaled across various benchmarks. For example, on SVGbench testing visual and structural reasoning, it ranked just behind GPT-4.1 Mini, nearly matching the capabilities of top-tier closed models. Meanwhile, on MMLU—a comprehensive test of broad language understanding—V3.1 held its ground against GPT-5.
But what truly captured attention was its affordability. Developers noted that tasks which previously cost approximately $70 on closed systems could now be performed for roughly $1. This 68-fold reduction in operational cost is poised to democratize AI deployment across startups, research institutions, and even individual developers, significantly lowering the barrier to entry in high-performance AI.