Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A developer is using the Vertex AI Gemini API to generate product descriptions. They get a 400 error 'INVALID_ARGUMENT: The model's maximum input token limit is 8192.' What is the most likely issue?
⚠ Common exam trap
Watch out — candidates often confuse input token limits with output token limits or general API authentication errors, but the specific error message 'maximum input token limit' directly points to prompt length as the root cause.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The prompt is too long
The 400 error 'INVALID_ARGUMENT: The model's maximum input token limit is 8192' explicitly indicates that the combined token count of the prompt (system instructions, user input, and any conversation history) exceeds the 8192-token context window of the Gemini model being used. This is a hard limit enforced by the Vertex AI Gemini API, and the error is triggered before any generation begins. Therefore, the most likely issue is that the prompt is too long.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The prompt is too long
Why this is correct
The 400 INVALID_ARGUMENT error explicitly names the 8192-token maximum input limit, so the submitted prompt exceeds that ceiling. Truncating or chunking the input resolves it; the constraint is input length, not output length or quota.
- ✗
The API key is invalid
Why it's wrong here
An invalid API key produces 401 UNAUTHENTICATED or 403 PERMISSION_DENIED before the request reaches the model. Key validation is the correct focus when credentials are missing, expired or lack scope, not when the service explicitly reports an input token overflow.
- ✗
The output tokens are too high
Why it's wrong here
The error names the input token limit, so the prompt itself exceeds 8192 tokens; output length is governed by a separate max-output-tokens parameter and would raise a different error. Output token limits matter when configuring response length, not when diagnosing an oversized request.
- ✗
The model is not available in the region
Why it's wrong here
A regional availability problem returns a 404 or unsupported-location error, not INVALID_ARGUMENT quoting a token limit. Region selection is the right consideration when deploying a model to a location that does not host it, which is unrelated to request size.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.