Practice LLM Engineer Basics MCQ questions with detailed explanations and clear answer validation. These MCQs help you revise core concepts, compare close options, and improve accuracy for interviews, certification exams, and technical screening rounds. Use this updated 2026 set to strengthen fundamentals and confidence.
Q51. Which statement about greedy decoding is most accurate?
Select an answer to check.
Answer: Always pick highest-prob token.
Here, Always pick highest-prob token. is the right choice. Fast; can be repetitive. It aligns directly with what the question asks about which statement about greedy decoding is most accurate. Competing choices sound plausible, but they miss the key condition.
Q52. How is greedy decoding best characterized?
Select an answer to check.
Answer: Always pick highest-prob token.
In this case, Always pick highest-prob token. is correct. Fast; can be repetitive. It aligns directly with what the question asks about how is greedy decoding best characterized. Competing choices sound plausible, but they miss the key condition.
Q53. Which option best describes beam search?
Select an answer to check.
Answer: Track top-N partial sequences.
The best option here is Track top-N partial sequences.. Better for translation; less for chat. It aligns directly with what the question asks about which option best describes beam search. Competing choices sound plausible, but they miss the key condition.
Q54. What is the primary purpose of beam search?
Select an answer to check.
Answer: Track top-N partial sequences.
For this question, Track top-N partial sequences. is correct. Better for translation; less for chat. It aligns directly with what the question asks about what is the primary purpose of beam search. Competing choices sound plausible, but they miss the key condition.
Q55. Which statement about beam search is most accurate?
Select an answer to check.
Answer: Track top-N partial sequences.
Track top-N partial sequences. is the correct answer here. Better for translation; less for chat. It aligns directly with what the question asks about which statement about beam search is most accurate. Competing choices sound plausible, but they miss the key condition.
Q56. How is beam search best characterized?
Select an answer to check.
Answer: Track top-N partial sequences.
Here, Track top-N partial sequences. is the right choice. Better for translation; less for chat. This matches the core idea being tested around how is beam search best characterized. Competing choices sound plausible, but they miss the key condition.
Q57. Which option best describes hallucinations?
Select an answer to check.
Answer: Model generates false content confidently.
In this case, Model generates false content confidently. is correct. Mitigate via RAG, grounding, eval. This matches the core idea being tested around which option best describes hallucinations. Competing choices sound plausible, but they miss the key condition.
Q58. What is the primary purpose of hallucinations?
Select an answer to check.
Answer: Model generates false content confidently.
The best option here is Model generates false content confidently.. Mitigate via RAG, grounding, eval. This matches the core idea being tested around what is the primary purpose of hallucinations. Competing choices sound plausible, but they miss the key condition.
Q59. Which statement about hallucinations is most accurate?
Select an answer to check.
Answer: Model generates false content confidently.
For this question, Model generates false content confidently. is correct. Mitigate via RAG, grounding, eval. This matches the core idea being tested around which statement about hallucinations is most accurate. Competing choices sound plausible, but they miss the key condition.
Q60. How is hallucinations best characterized?
Select an answer to check.
Answer: Model generates false content confidently.
Model generates false content confidently. is the correct answer here. Mitigate via RAG, grounding, eval. This matches the core idea being tested around how is hallucinations best characterized. Competing choices sound plausible, but they miss the key condition.
Q61. Which option best describes retrieval-augmented generation?
Select an answer to check.
Answer: Augment LLM with retrieved context.
Here, Augment LLM with retrieved context. is the right choice. Reduces hallucinations. That is exactly the concept behind which option best describes retrieval-augmented generation in this context. Competing choices sound plausible, but they miss the key condition.
Q62. What is the primary purpose of retrieval-augmented generation?
Select an answer to check.
Answer: Augment LLM with retrieved context.
In this case, Augment LLM with retrieved context. is correct. Reduces hallucinations. That is exactly the concept behind what is the primary purpose of retrieval-augmented generation in this context. Competing choices sound plausible, but they miss the key condition.
Q63. Which statement about retrieval-augmented generation is most accurate?
Select an answer to check.
Answer: Augment LLM with retrieved context.
The best option here is Augment LLM with retrieved context.. Reduces hallucinations. That is exactly the concept behind which statement about retrieval-augmented generation is most accurate in this context. Competing choices sound plausible, but they miss the key condition.
Q64. How is retrieval-augmented generation best characterized?
Select an answer to check.
Answer: Augment LLM with retrieved context.
For this question, Augment LLM with retrieved context. is correct. Reduces hallucinations. That is exactly the concept behind how is retrieval-augmented generation best characterized in this context. Competing choices sound plausible, but they miss the key condition.
Q65. Which option best describes a vector database?
Select an answer to check.
Answer: Stores and queries embeddings.
Stores and queries embeddings. is the correct answer here. Used in RAG. That is exactly the concept behind which option best describes a vector database in this context. Competing choices sound plausible, but they miss the key condition.
Q66. What is the primary purpose of a vector database?
Select an answer to check.
Answer: Stores and queries embeddings.
Here, Stores and queries embeddings. is the right choice. Used in RAG. It fits the requirement in the prompt about what is the primary purpose of a vector. Competing choices sound plausible, but they miss the key condition.
Q67. Which statement about a vector database is most accurate?
Select an answer to check.
Answer: Stores and queries embeddings.
In this case, Stores and queries embeddings. is correct. Used in RAG. It fits the requirement in the prompt about which statement about a vector database is most. Competing choices sound plausible, but they miss the key condition.
Q68. How is a vector database best characterized?
Select an answer to check.
Answer: Stores and queries embeddings.
The best option here is Stores and queries embeddings.. Used in RAG. It fits the requirement in the prompt about how is a vector database best characterized. Competing choices sound plausible, but they miss the key condition.
Q69. Which option best describes embeddings?
Select an answer to check.
Answer: Dense vectors representing text.
For this question, Dense vectors representing text. is correct. Used for similarity search. It fits the requirement in the prompt about which option best describes embeddings. Competing choices sound plausible, but they miss the key condition.
Q70. What is the primary purpose of embeddings?
Select an answer to check.
Answer: Dense vectors representing text.
Dense vectors representing text. is the correct answer here. Used for similarity search. It fits the requirement in the prompt about what is the primary purpose of embeddings. Competing choices sound plausible, but they miss the key condition.
Q71. Which statement about embeddings is most accurate?
Select an answer to check.
Answer: Dense vectors representing text.
Here, Dense vectors representing text. is the right choice. Used for similarity search. This is the most accurate statement for which statement about embeddings is most accurate. Competing choices sound plausible, but they miss the key condition.
Q72. How is embeddings best characterized?
Select an answer to check.
Answer: Dense vectors representing text.
In this case, Dense vectors representing text. is correct. Used for similarity search. This is the most accurate statement for how is embeddings best characterized. Competing choices sound plausible, but they miss the key condition.
Q73. Which option best describes function calling / tool use?
Select an answer to check.
Answer: LLM produces calls to external tools.
The best option here is LLM produces calls to external tools.. Enables agents. This is the most accurate statement for which option best describes function calling / tool. Competing choices sound plausible, but they miss the key condition.
Q74. What is the primary purpose of function calling / tool use?
Select an answer to check.
Answer: LLM produces calls to external tools.
For this question, LLM produces calls to external tools. is correct. Enables agents. This is the most accurate statement for what is the primary purpose of function calling. Competing choices sound plausible, but they miss the key condition.
Q75. Which statement about function calling / tool use is most accurate?
Select an answer to check.
Answer: LLM produces calls to external tools.
LLM produces calls to external tools. is the correct answer here. Enables agents. This is the most accurate statement for which statement about function calling / tool use. Competing choices sound plausible, but they miss the key condition.
Q76. How is function calling / tool use best characterized?
Select an answer to check.
Answer: LLM produces calls to external tools.
Here, LLM produces calls to external tools. is the right choice. Enables agents. It aligns directly with what the question asks about how is function calling / tool use best. The remaining choices fail because they don’t satisfy the full definition.
Q77. Which option best describes evaluation of LLMs?
Select an answer to check.
Answer: Mix automated metrics + human eval.
In this case, Mix automated metrics + human eval. is correct. Multiple dimensions. It aligns directly with what the question asks about which option best describes evaluation of llms. The remaining choices fail because they don’t satisfy the full definition.
Q78. What is the primary purpose of evaluation of LLMs?
Select an answer to check.
Answer: Mix automated metrics + human eval.
The best option here is Mix automated metrics + human eval.. Multiple dimensions. It aligns directly with what the question asks about what is the primary purpose of evaluation of. The remaining choices fail because they don’t satisfy the full definition.
Q79. Which statement about evaluation of LLMs is most accurate?
Select an answer to check.
Answer: Mix automated metrics + human eval.
For this question, Mix automated metrics + human eval. is correct. Multiple dimensions. It aligns directly with what the question asks about which statement about evaluation of llms is most. The remaining choices fail because they don’t satisfy the full definition.
Q80. How is evaluation of LLMs best characterized?
Select an answer to check.
Answer: Mix automated metrics + human eval.
Mix automated metrics + human eval. is the correct answer here. Multiple dimensions. It aligns directly with what the question asks about how is evaluation of llms best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q81. Which option best describes guardrails?
Select an answer to check.
Answer: Constraints on inputs/outputs.
Here, Constraints on inputs/outputs. is the right choice. Safety and policy enforcement. This matches the core idea being tested around which option best describes guardrails. The remaining choices fail because they don’t satisfy the full definition.
Q82. What is the primary purpose of guardrails?
Select an answer to check.
Answer: Constraints on inputs/outputs.
In this case, Constraints on inputs/outputs. is correct. Safety and policy enforcement. This matches the core idea being tested around what is the primary purpose of guardrails. The remaining choices fail because they don’t satisfy the full definition.
Q83. Which statement about guardrails is most accurate?
Select an answer to check.
Answer: Constraints on inputs/outputs.
The best option here is Constraints on inputs/outputs.. Safety and policy enforcement. This matches the core idea being tested around which statement about guardrails is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q84. How is guardrails best characterized?
Select an answer to check.
Answer: Constraints on inputs/outputs.
For this question, Constraints on inputs/outputs. is correct. Safety and policy enforcement. This matches the core idea being tested around how is guardrails best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q85. Which option best describes fine-tuning?
Select an answer to check.
Answer: Adapt pretrained model to a task.
Adapt pretrained model to a task. is the correct answer here. Smaller labeled datasets. This matches the core idea being tested around which option best describes fine-tuning. The remaining choices fail because they don’t satisfy the full definition.
Q86. What is the primary purpose of fine-tuning?
Select an answer to check.
Answer: Adapt pretrained model to a task.
Here, Adapt pretrained model to a task. is the right choice. Smaller labeled datasets. That is exactly the concept behind what is the primary purpose of fine-tuning in this context. The remaining choices fail because they don’t satisfy the full definition.
Q87. Which statement about fine-tuning is most accurate?
Select an answer to check.
Answer: Adapt pretrained model to a task.
In this case, Adapt pretrained model to a task. is correct. Smaller labeled datasets. That is exactly the concept behind which statement about fine-tuning is most accurate in this context. The remaining choices fail because they don’t satisfy the full definition.
Q88. How is fine-tuning best characterized?
Select an answer to check.
Answer: Adapt pretrained model to a task.
The best option here is Adapt pretrained model to a task.. Smaller labeled datasets. That is exactly the concept behind how is fine-tuning best characterized in this context. The remaining choices fail because they don’t satisfy the full definition.
Q89. Which option best describes LoRA?
Select an answer to check.
Answer: Low-rank adapters for parameter-efficient fine-tuning.
For this question, Low-rank adapters for parameter-efficient fine-tuning. is correct. Smaller and faster. That is exactly the concept behind which option best describes lora in this context. The remaining choices fail because they don’t satisfy the full definition.
Q90. What is the primary purpose of LoRA?
Select an answer to check.
Answer: Low-rank adapters for parameter-efficient fine-tuning.
Low-rank adapters for parameter-efficient fine-tuning. is the correct answer here. Smaller and faster. That is exactly the concept behind what is the primary purpose of lora in this context. The remaining choices fail because they don’t satisfy the full definition.
Q91. Which statement about LoRA is most accurate?
Select an answer to check.
Answer: Low-rank adapters for parameter-efficient fine-tuning.
Here, Low-rank adapters for parameter-efficient fine-tuning. is the right choice. Smaller and faster. It fits the requirement in the prompt about which statement about lora is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q92. How is LoRA best characterized?
Select an answer to check.
Answer: Low-rank adapters for parameter-efficient fine-tuning.
In this case, Low-rank adapters for parameter-efficient fine-tuning. is correct. Smaller and faster. It fits the requirement in the prompt about how is lora best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q93. Which option best describes RLHF?
Select an answer to check.
Answer: Reinforcement learning from human feedback.
The best option here is Reinforcement learning from human feedback.. Aligns to preferences. It fits the requirement in the prompt about which option best describes rlhf. The remaining choices fail because they don’t satisfy the full definition.
Q94. What is the primary purpose of RLHF?
Select an answer to check.
Answer: Reinforcement learning from human feedback.
For this question, Reinforcement learning from human feedback. is correct. Aligns to preferences. It fits the requirement in the prompt about what is the primary purpose of rlhf. The remaining choices fail because they don’t satisfy the full definition.
Q95. Which statement about RLHF is most accurate?
Select an answer to check.
Answer: Reinforcement learning from human feedback.
Reinforcement learning from human feedback. is the correct answer here. Aligns to preferences. It fits the requirement in the prompt about which statement about rlhf is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q96. How is RLHF best characterized?
Select an answer to check.
Answer: Reinforcement learning from human feedback.
Here, Reinforcement learning from human feedback. is the right choice. Aligns to preferences. This is the most accurate statement for how is rlhf best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q97. Which option best describes inference cost?
Select an answer to check.
Answer: Driven by tokens in + out × model size.
In this case, Driven by tokens in + out × model size. is correct. Optimize prompts and models. This is the most accurate statement for which option best describes inference cost. The remaining choices fail because they don’t satisfy the full definition.
Q98. What is the primary purpose of inference cost?
Select an answer to check.
Answer: Driven by tokens in + out × model size.
The best option here is Driven by tokens in + out × model size.. Optimize prompts and models. This is the most accurate statement for what is the primary purpose of inference cost. The remaining choices fail because they don’t satisfy the full definition.
Q99. Which statement about inference cost is most accurate?
Select an answer to check.
Answer: Driven by tokens in + out × model size.
For this question, Driven by tokens in + out × model size. is correct. Optimize prompts and models. This is the most accurate statement for which statement about inference cost is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q100. How is inference cost best characterized?
Select an answer to check.
Answer: Driven by tokens in + out × model size.
Driven by tokens in + out × model size. is the correct answer here. Optimize prompts and models. This is the most accurate statement for how is inference cost best characterized. The remaining choices fail because they don’t satisfy the full definition.