Your distinction between an overnight background task and an interactive chatbot makes the parameter-count comparison much more actionable. One extra constraint belongs in that decision: whether the model can finish the entire workload within the deadline, including retries and long inputs, rather than merely produce an acceptable answer in isolation.
I would compare candidates on completed tasks per available window, with the same input set and an explicit failure policy. A smaller model that needs several repair attempts can lose its apparent speed advantage. Conversely, a slower model may be entirely suitable when its first answer reliably completes the job.
Your distinction between an overnight background task and an interactive chatbot makes the parameter-count comparison much more actionable. One extra constraint belongs in that decision: whether the model can finish the entire workload within the deadline, including retries and long inputs, rather than merely produce an acceptable answer in isolation.
I would compare candidates on completed tasks per available window, with the same input set and an explicit failure policy. A smaller model that needs several repair attempts can lose its apparent speed advantage. Conversely, a slower model may be entirely suitable when its first answer reliably completes the job.