vercel/ai · error · InvalidArgumentError

Google batch input files must not exceed 2 GB.

Error message

Google batch input files must not exceed 2 GB.

What it means

Batch jobs upload requests as a single JSONL file to Google's Batch API, which caps input file size at 2 GB (googleBatchInputFileMaxBytes). experimental_doStartBatch checks the assembled Blob size before uploading and throws InvalidArgumentError if the file exceeds the limit, because Google would reject the upload anyway.

Solutions

  1. Split the requests into multiple batches, each under 2 GB, and start several batch jobs.
  2. Remove or shrink inline data (use Cloud Storage URIs / file references instead of base64) to reduce JSONL size.
  3. Trim prompts or move large static content out of per-request payloads (e.g. into context caching where supported).

Example fix

// before
await model.experimental_doStartBatch({ requests: allRequests }); // > 2GB
// after
for (const chunk of chunks(allRequests, 10_000)) {
  await model.experimental_doStartBatch({ requests: chunk });
}
Defensive patterns

Strategy: validation

Validate before calling

const MAX_BYTES = 2 * 1024 ** 3;
function validateBatchSize(requests) {
  const size = new Blob(requests.map(r => JSON.stringify(r) + '\n')).size;
  if (size > MAX_BYTES) throw new Error(`Batch payload ${size} bytes exceeds 2 GB; split into multiple batches.`);
  return size;
}

Type guard

null

Try / catch

try {
  await model.experimental_doStartBatch({ requests });
} catch (e) {
  if (e?.name === 'AI_InvalidArgumentError' && /2 GB/.test(e.message ?? '')) {
    // split requests into chunks and start multiple batch jobs
  } else throw e;
}

Prevention

When it happens

Trigger: Calling `model.experimental_doStartBatch({ requests })` (or the batch helper) with a request array whose serialized JSONL exceeds 2,147,483,648 bytes - typically very large prompts, inline file/image data, or simply too many requests.

Common situations: Batch-embedding large document corpora with inline attachments; long-running backfills of thousands of requests with big system prompts; accidentally embedding base64 media in batch requests.

Related errors

AI-assisted analysis of vercel/ai@69428b1f8b (2026-08-30). Data as JSON: /api/errors/a55134dc9c94aec8. Report an issue: GitHub.

Appendix: source

Thrown at packages/google/src/google-batch.ts:266

    if (fileParts == null) {
      const { value } = await postJsonToApi({
        url: createUrl,
        headers,
        body: inlineBatchBody,
        failedResponseHandler: googleFailedResponseHandler,
        successfulResponseHandler: createJsonResponseHandler(
          googleBatchOperationSchema,
        ),
        abortSignal: options.abortSignal,
        fetch: this.batchConfig.fetch,
      });
      operation = value;
    } else {
      const inputFile = new Blob(fileParts, { type: 'application/jsonl' });
      // Blob snapshots the strings, so release the potentially large input array.
      fileParts.length = 0;
      if (inputFile.size > googleBatchInputFileMaxBytes) {
        throw new InvalidArgumentError({
          argument: 'requests',
          message: 'Google batch input files must not exceed 2 GB.',
        });
      }

      const { value: uploadUrl } = await postJsonToApi({
        url: `${this.getBaseOrigin()}/upload/v1beta/files`,
        headers: combineHeaders(headers, {
          'X-Goog-Upload-Protocol': 'resumable',
          'X-Goog-Upload-Command': 'start',
          'X-Goog-Upload-Header-Content-Length': String(inputFile.size),
          'X-Goog-Upload-Header-Content-Type': 'application/jsonl',
        }),
        body: {
          file: {
            display_name: `${displayName}-input`,
          },
        },

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