A & B is correct answer.
A: smaller batch size will increase the potential of update child records with the same parent. It may cause record-locking errors.
We have this limitation: Up to 5 batch jobs can be queued or active concurrently.
So no error like: "Too many concurrent batches" because only 5 batch jobs run at a time => C & D: wrong.
https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_batch_interface.htm

AC

Reducing the batch size from 2000 to a smaller number can help avoid the "Max CPU time exceeded" error. However, this can also introduce other issues such as record-locking errors, which occur when two or more parallel jobs are trying to update the same record at the same time. The smaller batch size can also increase the number of concurrent batches, potentially triggering the "Too many concurrent batches" error if the maximum number of concurrent API requests is exceeded.

It is important to consider the trade-off between batch size and performance, and to find the optimal balance that works for the specific use case. This may involve monitoring the system behavior, adjusting the batch size as needed, and fine-tuning other configuration settings such as API request limits.

Increasing or reducing batch size will have no impact on number of API request, because Bulk API transfer the data to server and then process the request. That’s where the batch size comes to picture.

Answer should be A,B

The answer should be B and D

https://help.salesforce.com/s/articleView?id=000338933&type=1