Part 6/8:
Despite its promising capabilities, there are aspects of qwq 32b that warrant scrutiny. Firstly, its 132k context window is on the smaller side given industry standards, potentially limiting its functional range in certain complex tasks. Furthermore, the model’s propensity for extensive “thinking” could lead to higher token usage, raising concerns around efficiency.
Notably, insights gathered from earlier methodologies, such as Chain of Thought prompting, may serve as a solution to mitigate excessive token consumption while maintaining critical output.