microsoft/Phi-3-small-128k-instruct · Slower generation with multi-batch size.

I am trying to batch my inference process but observing slower speeds when i set batch size > 1.
Code:

output = model.generate(input_ids=input_ids,
                          max_new_tokens=args.max_gen_seq_length,
                          do_sample=True,
                          temperature=args.temp,
                          top_k=args.topk, 
                          top_p=args.topp, 
                          repetition_penalty=args.repetition_penalty,
                          pad_token_id=tokenizer.pad_token_id,
                          attention_mask=attention_mask)

Params:
temperature: 0.1
top_k=50
top_p=0.95
repetition_penalty=1.1

When I run this code with batch size 1 where my input isnt padded and there is no attention mask supplied, the time taken on average is 8-9 secs.

But when I run this code with batch size 2 where my input is padded to 4500 tokens and a corresponding attention mask is supplied, the time taken on average is 21 secs, which is slower than running two sequential batches of size 1.

Is this expected in these settings?