Kimi and Moonshot AI Quiz

Answers and explanations appear as you take the quiz.

1. What maximum context size did Moonshot announce for the moonshot-v1 API at its January 2024 public beta?
   • Up to 128K tokens
   • Up to 8K tokens
   • Up to 32K tokens
   • Up to 1M tokens
2. When does Moonshot AI’s official timeline say the company was founded?
   • Spring 2018
   • Spring 2023
   • Fall 2020
   • Winter 2025
3. Which major investor did Alibaba disclose in its FY2024 annual report?
   • OpenAI, with an approximately 36% equity interest
   • Anthropic, with an approximately 36% equity interest
   • Moonshot AI, with an approximately 36% equity interest reported for that fiscal year
   • DeepMind, with an approximately 36% equity interest
4. What architecture do later Kimi models such as K2 use to stay efficient at large scale?
   • Pure recurrent networks
   • Decision trees
   • Support vector machines
   • Mixture-of-experts (MoE)
5. What was Kimi k1.5, released in early 2025, designed to improve?
   • Step-by-step reasoning
   • Image upscaling
   • Battery efficiency
   • 3D rendering
6. Why is a long context window practically useful?
   • It reduces the model's parameter count
   • It lets the model consider an entire long document at once
   • It eliminates the need for training data
   • It guarantees factual accuracy
7. What scale does the Kimi K2 technical report give for total and activated parameters?
   • 70 billion total, with all 70 billion activated
   • 7 billion total, with 32 billion activated
   • 1 trillion total parameters, with 32 billion activated
   • 1 trillion total, with all parameters activated for every token
8. Why should a comparison of Kimi model capabilities identify the exact release?
   • Every release has identical capabilities
   • The product name alone establishes the model’s benchmark score
   • Version identifiers matter only for billing
   • Context limits, modalities, and tool behavior can differ across model versions