I have checked ML flow code and error message is also different. So I think this is the limitation of databricks side.

except requests.exceptions.Timeout as to:
raise MlflowException(
f"API request to {url} failed with timeout exception {to}."
" To increase the timeout, set the environment variable "
f"{MLFLOW_HTTP_REQUEST_TIMEOUT!s} to a larger value."

https://github.com/mlflow/mlflow

DBX limitation
>Model execution duration Per request 120 seconds
https://docs.databricks.com/en/machine-learning/model-serving/model-serving-limits.html