How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications

Researchers improved a Portuguese essay grading system based on the Qwen3-4B model by redesigning its tokenizer vocabulary to focus on token cost rather than frequency, reducing inference costs by 77% without changing the model itself.