AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-model-families-small-models-haiku-flash-mini-r8a1-creators

1. What is the core idea behind "AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer"?

   1. Small models are not just cheap — for narrow, high-volume tasks they are often faster, more predictable, and easier to reason about than their big siblings.
   2. How quantization shrinks AI models for deployment — and where quality breaks.
   3. Provide instant autocomplete with no network round-trip
   4. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.

2. Which term best describes a foundational idea in "AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer"?

   1. Haiku
   2. small model
   3. Flash
   4. escalation router

3. A learner studying AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer would need to understand which concept?

   1. small model
   2. Flash
   3. Haiku
   4. escalation router

4. Which of these is directly relevant to AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. small model
   2. Haiku
   3. escalation router
   4. Flash

5. Which of the following is a key point about AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. Identify small-model-friendly task patterns
   2. Show the cost and latency delta
   3. Recommend a 'small first, escalate' router
   4. Note where small models genuinely fail

6. Which of these does NOT belong in a discussion of AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. Recommend a 'small first, escalate' router
   2. Show the cost and latency delta
   3. How quantization shrinks AI models for deployment — and where quality breaks.
   4. Identify small-model-friendly task patterns

7. Which statement is accurate regarding AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. Predict where small-model quality cliffs sit
   2. Account for tokens-per-minute quotas across tiers
   3. Replace evals on your specific data
   4. How quantization shrinks AI models for deployment — and where quality breaks.

8. What is the key insight about "Prompt: smallest sufficient model" in the context of AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. How quantization shrinks AI models for deployment — and where quality breaks.
   2. Provide instant autocomplete with no network round-trip
   3. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.
   4. List your tasks and current model. Ask: 'For each, recommend the smallest model that should suffice and the eval to conf…

9. What is the key insight about "Quality cliffs are real" in the context of AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

   1. Small models drop off sharply on multi-hop reasoning, long context, and ambiguous instructions.
   2. How quantization shrinks AI models for deployment — and where quality breaks.
   3. Provide instant autocomplete with no network round-trip
   4. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.

10. Which statement accurately describes an aspect of AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

    1. How quantization shrinks AI models for deployment — and where quality breaks.
    2. Defaulting to the biggest model wastes money and latency; small models excel at classification, extraction, routing, and reformatting at a f…
    3. Provide instant autocomplete with no network round-trip
    4. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.

11. Which best describes the scope of "AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer"?

    1. It is unrelated to model-families workflows
    2. It applies only to the opposite beginner tier
    3. It focuses on Small models are not just cheap — for narrow, high-volume tasks they are often faster, more predicta
    4. It was deprecated in 2024 and no longer relevant

12. Which section heading best belongs in a lesson about AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

    1. How quantization shrinks AI models for deployment — and where quality breaks.
    2. Provide instant autocomplete with no network round-trip
    3. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.
    4. What AI does well here

13. Which section heading best belongs in a lesson about AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

    1. What AI cannot do
    2. How quantization shrinks AI models for deployment — and where quality breaks.
    3. Provide instant autocomplete with no network round-trip
    4. Old model 'gpt-3.5-turbo' is being deprecated — your code calling it will break.

14. Which of the following is a concept covered in AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

    1. Haiku
    2. small model
    3. Flash
    4. escalation router

15. Which of the following is a concept covered in AI Model Families: When Small Models (Haiku, Flash, Mini) Are the Right Answer?

    1. small model
    2. Flash
    3. Haiku
    4. escalation router