What is the Gemini Batch API and when should you use it?

The Batch API allows submitting multiple Gemini API requests as an asynchronous batch job, receiving results up to 24 hours later at approximately 50% reduced cost compared to synchronous API calls. It is designed for large-scale, non-time-sensitive workloads.

from google import genai
from google.genai import types

client = genai.Client()

# Create a batch job with multiple requests:
batch = client.batches.create(
    model="gemini-2.5-flash",
    src=types.CreateBatchJobSource(
        requests=[
            types.EmbedContentRequest(
                content=types.Content(parts=[types.Part(text="Summarise: " + doc)])
            )
            for doc in list_of_1000_documents
        ]
    ),
)
print(f"Batch ID: {batch.name}, state: {batch.state}")

# Poll for completion (up to 24 hours):
import time
while batch.state in ("JOB_STATE_PENDING", "JOB_STATE_RUNNING"):
    time.sleep(60)
    batch = client.batches.get(name=batch.name)

# Retrieve results:
for result in client.batches.list_responses(name=batch.name):
    print(result.response.candidates[0].content.parts[0].text)

# All current Gemini 3 and 2.5 models support the Batch API

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