AIF-C01 Applications of Foundation Models Practice Question

Exhibit

Refer to the exhibit.
{
  "completion": "The capital of France is Paris. The capital of Germany is Berlin. The capital of",
  "stop_reason": "max_tokens",
  "usage": {
    "input_tokens": 10,
    "output_tokens": 30
  }
}

Refer to the exhibit. You receive this response from Amazon Bedrock. What is the most likely cause of the incomplete information?

⚠ Common exam trap

AWS often tests the distinction between output truncation (max_tokens) and output quality issues (temperature, prompt engineering), so the trap here is that candidates may incorrectly attribute a truncated response to model ignorance or randomness rather than the explicit token limit.

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 max_tokens limit was reached

The response from Amazon Bedrock shows an incomplete sentence that cuts off mid-thought, which is a classic symptom of hitting the max_tokens limit. When the generated output reaches the specified maximum number of tokens, the model stops generating immediately, resulting in truncated text. This is the most likely cause because the output is syntactically incomplete but otherwise coherent up to the cutoff point.

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 max_tokens limit was reached
Why this is correct
stop_reason: max_tokens indicates the output was capped by the token limit.
✗
The prompt was too short
Why it's wrong here
Short prompts can cause incomplete answers, but the stop_reason explicitly shows max_tokens.
✗
The temperature was too high
Why it's wrong here
Temperature affects randomness, not truncation.
✗
The model lacks knowledge about capitals
Why it's wrong here
The model correctly started listing capitals; missing data is due to truncation.

Go deeper

AIF-C01 Applications of Foundation Models Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

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