How to speed up Blenderbot inference with Sagemaker?

When I hit the inference API for the Blenderbot-400M-distill model, I get a response within 3 seconds. However, when I try to deploy the model on AWS Sagemaker, my prediction times range to about 10 seconds irrespective of whether I use a compute-optimized instance or a memory-optimized one.

from sagemaker.huggingface import HuggingFaceModel
import sagemaker

role = sagemaker.get_execution_role()
# Hub Model configuration.
hub = {

# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(

# deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
	initial_instance_count=1, # number of instances
	instance_type='ml.m4.4xlarge' # ec2 instance type

	'inputs': {
		"past_user_inputs": ["Which movie is the best ?"],
		"generated_responses": ["It's Die Hard for sure."],
		"text": "Can you explain why ?"

I have even tried this with ml.c5.4xlarge and ml.m6g.4xlarge instances. The predicition time doesn’t improve.

Any suggestions would be really appreciated!

Reference: Amazon SageMaker Pricing - Machine Learning - Amazon Web Services