Code execution

A Code Interpreter That Runs What It Writes

Unexecuted code is a hypothesis.

The single biggest quality difference in AI-assisted programming is whether the model sees its own output fail. A code interpreter closes that loop: it writes the code, runs it, reads the actual error, and fixes the actual problem — rather than producing a plausible-looking function and leaving verification to you.

What execution changes

Syntax and import errors are caught and fixed before you ever see them.
Logic errors surface as wrong output rather than as a bug you find on Thursday.
Data analysis returns real numbers computed from your file, not estimates from a language model.
Charts are rendered from the actual data rather than described.
"It works" becomes a claim backed by output you can read.

Common jobs it handles well

Data analysis — load a CSV or spreadsheet, clean it, compute statistics, plot the result.
Algorithm work — write the function, run it against edge cases, iterate until they pass.
Debugging — paste the failing code and the real traceback and let it reproduce the failure.
Format conversion and data wrangling between JSON, CSV and tabular formats.
Quick maths and simulations where a language model would otherwise guess.
Generating and running the test that proves a fix holds.

Getting more out of it

State the language and version. Behaviour differs enough to matter.
Upload the real data file rather than describing its shape.
Ask for the diagnosis before the fix — an explanation is evidence of understanding.
Ask it to print intermediate values when a result looks wrong.
If two attempts fail, switch to a different model in the same thread rather than re-prompting the same one.
Finish by asking for the regression test.

The boundaries

It runs in a sandbox — no access to your local machine, your network or your production systems.
Long-running or very heavy computation is not what this is for.
It cannot install arbitrary system-level dependencies.
Never paste credentials, keys or customer data into a prompt.
Review generated code before it goes anywhere near production, as you would any contribution.

Models you can use for this

MiMo-V2-Flash256K

DeepSeek-V3.2 (Reasoning)128K

DeepSeek-V3.2128K

Qwen3-Max256K

Qwen3.5-Plus1M

Command A Reasoning256K

Command A256K

MiniMax M2197K

See all 8+ models and specs

Frequently asked questions

What languages does the code interpreter support?

It covers the major languages used for analysis, scripting and general programming, with Python being the most common for data work.

Does it run code on my computer?

No. Execution happens in an isolated sandbox with no access to your local machine, network or production systems.

Can it analyse my spreadsheet or CSV?

Yes. Upload the file and it will load, clean and analyse the real data, returning computed results and rendered charts rather than estimates.

Is it better than asking a model to write code?

Substantially, because it sees its own failures. A model that never runs its output cannot distinguish code that works from code that reads as though it should.

Can I use different models with it?

Yes — all 50+ models are available in the same thread, so if one model keeps missing a bug you can hand it to a different lab without re-explaining the problem.

Keep reading

See the output, not a promise

Write, execute and debug in one thread across 50+ models. Start free.