Gemini Batch API jobs with gemini-3.1-flash-preview do not reach SUCCEEDED after 24+ hours

[grhan17]

Description

Since approximately 2026-09-15, Gemini Developer API (AI Studio API) batch jobs using gemini-3.1-flash-preview have not transitioned to JOB_STATE_SUCCEEDED, even after more than 24 hours.

The jobs are created successfully, but polling them with client.batches.get() continues to return a non-terminal state without a useful error. This started suddenly in a production catalog-processing pipeline; the same integration had previously completed batch jobs normally.

This appears similar to past incidents reported in:

• Gemini Batch API stuck all jobs on BATCH_STATE_PENDING for more than 24 hours #1482
• Gemini 2.5 Pro Batch API: Jobs stuck in PENDING/RUNNING for over 24 hours #2221

Both previous issues are closed, so I am reporting this as a possible recurrence.

Environment

• API: Gemini Developer API / Google AI Studio API (not Vertex AI)
• Language: Python
• SDK: google-genai==1.60.0
• Model: models/gemini-3.1-flash-preview
• Input: JSONL file uploaded through the Files API
• First observed: 2026-09-15

Minimal flow

import os
from google import genai

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

uploaded_file = client.files.upload(
    file="input.jsonl",
    config={"mime_type": "jsonl"},
)

job = client.batches.create(
    model="models/gemini-3.1-flash-preview",
    src=uploaded_file.name,
    config={"display_name": "batch-test"},
)

# Still does not reach JOB_STATE_SUCCEEDED after 24+ hours
current_job = client.batches.get(name=job.name)
print(current_job.state)

Expected behavior

The batch job should complete within the documented processing window, or fail with an actionable error.

Actual behavior

The job remains in a non-terminal state for more than 24 hours and does not produce output or an actionable error.

Additional information

We can provide affected batch job names privately to maintainers if needed, but have omitted account/project identifiers and job IDs from this public report.

Could you confirm whether there is a current service-side incident or elevated queueing for Gemini Developer API batch jobs using gemini-3.1-flash-preview?

[grhan17]

Additional reports from the Google AI Developers Forum suggest this may be a broader Batch API incident during the same time window:

• Gemini 3.1 Pro Batch jobs stuck with zero requests processed across two Tier 2 projects — reported on September 15. Other users in the thread report the same behavior with gemini-3.1-flash-image and gemini-3.6-flash, beginning around the evening of September 14.
• Batch API stuck in RUNNING for 24+ hours, then "Internal error encountered" — reported on September 16 with gemini-3.5-flash-lite. The affected jobs eventually reached SUCCEEDED, but all output entries contained Internal error encountered. The reporter later noted that newly submitted jobs had started processing normally again.

The models are not identical to ours, but the timing and Batch API behavior are closely aligned: jobs are accepted, remain in BATCH_STATE_RUNNING with no processing for many hours, while non-batch requests continue to work. This suggests a possible service-side Batch scheduling or processing incident rather than an SDK-specific issue.

[Venkaiahbabuneelam]

Hi @grhan17, Thank you for bringing this to our attention.

We have tested and confirmed that stable models (such as gemini-3.5-flash and gemini-3.5-flash-lite) complete successfully without issues.

Thanks