Mistral Codestral 25 — code-specific model

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-modelx-codestral-25-builders

1. What is the primary use case that Codestral 25 was designed for?

   1. Generating images from text descriptions
   2. Analyzing large datasets visually
   3. Answering general knowledge questions in chat
   4. Inline code completion within IDEs

2. What does FIM stand for in the context of code completion models?

   1. Fast iteration mode
   2. Fill-in-the-middle
   3. Function integration method
   4. File indexing mechanism

3. Which characteristic allows Codestral 25 to run on every keystroke of a developer?

   1. Its integration with video editing tools
   2. Its very low cost per completion
   3. Its support for 80+ languages
   4. Its ability to generate images

4. What hardware requirement is mentioned as an advantage of Codestral 25's size?

   1. A single consumer-grade GPU can serve a whole team's traffic
   2. It only runs on specialized AI hardware
   3. It requires a supercomputer cluster
   4. It needs at least 8 GPUs in parallel

5. How many programming languages does Codestral 25 claim to support at usable quality?

   1. About 200 languages
   2. Fewer than 10 languages
   3. Exactly 5 languages
   4. Over 80 languages

6. What is the approximate latency per completion for Codestral 25 according to the comparison table?

   1. 5-10 seconds
   2. Exactly 1 second
   3. Less than 500 milliseconds
   4. 1-2 seconds

7. Which of these is listed as a key term in the lesson?

   1. Image generation
   2. Voice synthesis
   3. Text classification
   4. Latency budget

8. What type of tasks does Codestral 25 underperform on compared to chat-tier models?

   1. Image recognition
   2. Basic text formatting
   3. Simple arithmetic calculations
   4. Multi-step refactors and natural-language explanations

9. Which IDE integrations ship with Codestral 25 as an option?

   1. Notepad++, Eclipse, and PyCharm
   2. VS Code, Sublime Text, and Atom
   3. Continue, Tabby, and Zed
   4. Visual Studio, IntelliJ, and Vim

10. What deployment options are available for Codestral 25?

    1. Mistral API and self-hosted
    2. Only available on Apple devices
    3. Only available through Microsoft Azure
    4. Only available as a mobile app

11. In the comparison table, what is noted about Claude Sonnet 4.6's FIM support?

    1. It has native FIM support
    2. FIM support is not mentioned for Claude
    3. It requires a workaround
    4. It does not support FIM at all

12. What is described as the 'different class of tool' compared to a chat assistant?

    1. GPT-5 as a general-purpose model
    2. Any self-hosted language model
    3. Codestral 25 as an inline autocomplete tool
    4. Claude Sonnet as a conversational AI

13. What specific capability does the lesson say Codestral 25 excels at?

    1. Music composition
    2. Stock market prediction
    3. Video game playing
    4. Code completions

14. What does the lesson suggest about verifying product details since this model was reviewed?

    1. The model is no longer available
    2. Prices, availability, and policy details may have changed
    3. The lesson content is guaranteed accurate forever
    4. The model was discontinued in 2025

15. Based on the latency comparison, which model would be more suitable for a real-time code completion feature?

    1. Claude Sonnet 4.6 due to its advanced reasoning
    2. Codestral 25 due to sub-500ms latency
    3. Neither model supports real-time completion
    4. Either model would work equally well