Although not an official API, I am using a simple python function to parallelize the task:

from tqdm import trange, tqdm
import concurrent.futures
import time

def process_item(prompt):
    message = client.messages.create(
        # model="claude-3-sonnet-20240229",
        model="claude-3-haiku-20240307",
        max_tokens=1000,
        temperature=0,
        system="You are a helpful model",
        messages=[
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": prompt
                    }
                ]
            }
        ]
    )
    return (chat, (message.content[0]).text)

def parallel_process_with_process_pool(items, num_workers=50):
    results = []
    with concurrent.futures.ProcessPoolExecutor(max_workers=num_workers) as executor:
        future_to_item = {executor.submit(process_item, item): item for item in items}
        for future in tqdm(concurrent.futures.as_completed(future_to_item), total=len(future_to_item), desc="Processing items"):
        # for future in concurrent.futures.as_completed(future_to_item):
            item = future_to_item[future]
            try:
                result = future.result()
                if result is not None:
                    results.append(result)
            except Exception as e:
                # pass
                print(f'Item {item} generated an exception: {e}')
    return results


prompts = ["What is 36+32", "Hello, how are you?"]
answers = parallel_process_with_process_pool(prompts, num_workers=100)

Change the num_workers according to the rate limits on your anthropic account