[Question]: Why is running MInference/examples/run_vllm.py not as fast as running vllm alone?

Describe the issue

from vllm import LLM, SamplingParams

from minference import MInference

prompts =  [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
]

prompts = prompts*100

sampling_params = SamplingParams(
    temperature=0.8,
    top_p=0.95,
    max_tokens=10,
)
model_name = "Qwen/Qwen2-7B-Instruct/"

llm = LLM(
    model_name,
    max_num_seqs=1,
    enforce_eager=True,
    
)

# Patch MInference Module
minference_patch = MInference("vllm", model_name)
llm = minference_patch(llm)

outputs = llm.generate(prompts, sampling_params)


import time
t1 = time.time()

# Print the outputs.
for output in outputs:
    prompt = output.prompt
    generated_text = output.outputs[0].text
  
t2 = time.time()

print('minference_time:',t2-t1)


print('=============================================================================')


from vllm import LLM, SamplingParams

from minference import MInference

prompts =  [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
]

prompts = prompts*100


sampling_params = SamplingParams(
    temperature=0.8,
    top_p=0.95,
    max_tokens=10,
)
model_name = "Qwen/Qwen2-7B-Instruct/"


llm = LLM(
    model_name,
    max_num_seqs=1,
    enforce_eager=True,
    
)

# Patch MInference Module
#minference_patch = MInference("vllm", model_name)
#llm = minference_patch(llm)

outputs = llm.generate(prompts, sampling_params)


import time
t1 = time.time()

# Print the outputs.
for output in outputs:
    prompt = output.prompt
    generated_text = output.outputs[0].text
  
t2 = time.time()

print('vllm_time:',t2-t1)

result:
minference_time:0.0003895759582519531s
vllm_time:0.0002791881561279297s
Why is minference_time greater than vllm_time?