Best AI for coding classes: Claude vs GPT vs DeepSeek vs Gemini

There's a trap in using AI for a coding class. It can write the whole assignment in seconds, and if you let it, you'll pass the assignment and fail the exam. The useful question isn't which model writes the best code. It's which one helps you learn to write it.

Here's how the main options compare for CS courses: Claude (Sonnet 5.5 and Opus 5.5), ChatGPT (GPT-6.1 Sol and GPT-6 Astra), DeepSeek (V4.1 Flash and V4 Pro) and Gemini (3.8 Flash and 3.1 Pro).

The short version

Claude: the patient explainer

For learning, Claude is the one I'd start with. Ask it why your code fails and it tends to walk through what the program actually does, step by step, rather than just handing back a fixed version. It is also good at saying "this part of my answer is a guess".

Claude Opus 5.5 is particularly good when it can see several files at once and has to trace a bug across them, which is what a group project or a larger assignment looks like. Sonnet 5.5 is plenty for single-file questions.

Here's my function and the error message. Don't fix it. Explain what the code does line by line with this input, and stop at the line where it goes wrong. Then give me a hint, not the answer.

ChatGPT: fast, confident, strong on hard problems

GPT-6.1 Sol is quick and gives tidy, well-formatted answers, which suits "what does this keyword do" and "show me three ways to loop over a dictionary". GPT-6 Astra is OpenAI's model for the hardest reasoning, maths and code, and it's very good at algorithmic problems.

The downside for learning is the same as the upside: confidence. It will give you a clean answer quickly, and it's easy to paste it in without understanding it.

I'm learning recursion. Give me a problem slightly harder than computing a factorial, let me try it, and then review my attempt. Point out the base case and the recursive case in my code.

DeepSeek: good value for reasoning

DeepSeek V4 Pro works through problems methodically and is good value for maths, logic and code that needs reasoning. V4.1 Flash costs very little per message, so it suits the steady stream of small questions a programming course produces.

Its limits are worth knowing. On LazySusan it's text only, so screenshots of errors or diagrams need another model, and it accepts prompts up to 128K tokens, which is less than the others. For a single assignment that's usually fine.

Trace this algorithm by hand on the input [3, 1, 2]. Show the state of every variable after each step in a table.

Gemini: big inputs and mixed files

Gemini takes in a lot at once: a long project, a PDF of the assignment spec, a screenshot of the expected output. Gemini 3.8 Flash is quick and cheap for a first look; Gemini 3.1 Pro is the one for harder reasoning.

The PDF is my assignment spec and the attached files are my code. List every requirement in the spec and tell me which ones my code meets, which it misses, and where.

That prompt is about checking your work against the spec, not writing it, and it catches the "I forgot about the edge case in section 3" mistake.

Using AI in a way that actually teaches you

Some patterns that help:

• Ask for hints, not answers. "Give me one hint" is the most useful phrase in a CS course.
• Explain your code back. Paste your solution and say: "I'll explain how this works. Tell me where my explanation is wrong."
• Predict, then run. Ask the model what your code will print, guess yourself first, then run it. You learn from the difference.
• Ask for tests, not fixes. "Write five test cases this function should pass, including two edge cases" makes you do the fixing.
• Compare two explanations. When something doesn't click, ask two models. Multi-Chat on LazySusan sends the same question to several models and shows the answers side by side, so you can see two ways of explaining the same idea. It runs on desktop and larger screens.

And always run the code. Models write code that looks right and isn't. The compiler and your tests are the final word, not the chat.

Where each one falls short

• Claude can over-explain when you wanted a one-line answer.
• ChatGPT can be confidently wrong, and its fixes are easy to paste without understanding.
• DeepSeek can't see images on LazySusan and has less room for very large inputs.
• Gemini Flash is quick and literal; for a subtle bug, step up to 3.1 Pro or ask Claude.
• All of them can produce code that uses a library version or function your course doesn't allow, so tell them the language version and what you're allowed to use.

The verdict

• Best for learning: Claude. It explains rather than just fixes.
• Best for hard algorithmic problems: GPT-6 Astra, with DeepSeek V4 Pro as the good-value alternative.
• Best for lots of small questions: DeepSeek V4.1 Flash or Gemini 3.8 Flash.
• Best for a big project or spec in one go: Gemini or Claude.

You don't need four subscriptions to use them. On LazySusan every plan includes all of them, from $8 a month, with a Student plan for .edu emails. More on each: Claude, ChatGPT, DeepSeek, Gemini, and the head-to-head DeepSeek vs ChatGPT. If your prompts keep getting finished code when you wanted a hint, Prompt School covers how to ask for what you need.

Use it honestly

• Read your course's AI policy. CS courses differ a lot: some allow AI for debugging, some ban it for graded work, some require you to say which prompts you used.
• Don't submit AI-written code as your own where it isn't allowed. Code is easy to compare, and you'll be asked to explain it in an exam either way.
• Check and test everything. AI-written code can be subtly wrong, insecure or use things your course forbids.
• Keep your learning ahead of the tool. If you can't write it without the model, you haven't learnt it yet.

See the plans or sign up to try them side by side.