DeepSeek: DeepSeek V3.1 Base

DeepSeek-V3.1 Base demonstrates exceptional speed, consistently ranking among the fastest models available, and offers highly competitive pricing across various benchmarks. As a base model, it is designed for raw next-token prediction rather than direct instruction following, which is evident in its benchmark performance. In coding, it achieved 58.3% accuracy, placing it in the 27th percentile, with a cost efficiency in the 91st percentile. However, its performance in instruction following and reasoning tasks was 0.0% accuracy, highlighting its nature as a base model not fine-tuned for such directives. Email classification showed a 33.3% accuracy (7th percentile), indicating a weakness in nuanced classification without specific fine-tuning. Ethics and general knowledge benchmarks yielded 50.0% and 36.4% accuracy respectively, both in the lower percentiles for accuracy but with excellent cost efficiency (98th percentile for both). The model's strengths lie in its foundational capabilities, speed, and cost-effectiveness, while its primary weakness is its inability to directly follow complex instructions or perform high-accuracy classification and reasoning without further fine-tuning, as expected from a base model.