# What is a code execution tool?

A code execution tool is a tool an LLM calls to run the code it writes, returning the output so the model can use it in its answer.

**You can host the tool yourself in a Runtime sandbox, for any model, with the
internet on your terms and a bill per second of real use.** A new sandbox ran
its first Python command 351 ms after the create request at the median on
24 September 2026 ([speed](/docs/speed)), fast enough to start one per call.

## Why it matters for AI agents

A model predicts text; it does not compute. Asked to sum a column or parse a
log, it guesses. Given a tool that runs code, it writes a short program, reads
the real result and answers from that. The same tool lets an agent test a
patch, convert a file or draw a chart.

Tools come in two kinds, and the difference decides who runs the code:

- **A server tool** runs on the model provider's side. You add it to the
  request and the provider runs the code in its own container. Anthropic's code
  execution tool is one: "The API runs every command server-side and returns
  the results to Claude within the same request".
- **A client tool** is one you define. The model returns a call, your code
  runs it wherever you choose, and you send the result back. A sandbox is the
  usual place, because the code came from a model.

## Hosted tools in facts

| Tool                          | Where the code runs                                 | Documented limits                                           |
| ----------------------------- | --------------------------------------------------- | ----------------------------------------------------------- |
| Anthropic code execution tool | Anthropic's container, 1 CPU, 5 GiB RAM, 5 GiB disk | Internet "completely disabled"; pre-installed packages only |
| Anthropic pricing             | 1,550 free hours a month per organization           | Then $0.05 an hour per container, 5-minute minimum          |
| OpenAI Code Interpreter tool  | "A fully sandboxed virtual machine"                 | Python; memory 1g (default), 4g, 16g or 64g                 |
| OpenAI container lifetime     | Expires after 20 minutes unused                     | Later calls to it fail                                      |
| Your own tool on Runtime      | A Firecracker microVM per sandbox                   | Size, packages, network and lifetime set per sandbox        |

Anthropic's code execution is free when the same request also includes its web
search or web fetch tool.

## Build one as a client tool

Give the model a tool such as `run_code(command)` and back it with a sandbox.
`withruntime/tools` hands you the tool already written, with a name, a
description, a JSON Schema and a function:

```ts check
import { Sandbox } from "withruntime";
import { sandboxTools } from "withruntime/tools";

await using sbx = await Sandbox.create({ network: { internet: false } });
const [exec] = sandboxTools(sbx);
console.log(exec.name, exec.description);
console.log(await exec.execute({ command: "python3 -c 'print(6 * 7)'" }));
```

```python check
from withruntime import Sandbox
from withruntime.tools import sandbox_tools

with Sandbox.create(network={"internet": False}) as sbx:
    run, read, write, ls = sandbox_tools(sbx)
    print(run("python3 -c 'print(6 * 7)'"))
```

Pass the schema to any model's tool format, run `execute` when the model calls
it, and return the output. Adapters for the OpenAI Agents SDK, the Vercel AI
SDK, the Claude Agent SDK, LangChain and others wrap the same tools
([frameworks](/docs/frameworks)).

## Runtime's side of the tool

- **Any model,** since the sandbox is yours and the tool is ordinary code.
- **Network rules** that allow a package index, deny everything, or switch the
  internet off, enforced on the host.
- **Any package or image,** with `pip`, `npm` and `sudo apt-get` working.
- **Cost:** $0.025 per vCPU-hour of measured CPU and $0.0075 per GiB-hour of
  memory, with no minimum ([pricing](/docs/pricing)).

For notebook-style sessions that keep variables and return charts, see
[code interpreter](/glossary/code-interpreter).

## Related

- [Claude code execution tool alternative](/compare/claude-code-execution-tool-alternative)
- [OpenAI Code Interpreter alternative](/compare/openai-code-interpreter-alternative)
- [What is a code interpreter?](/glossary/code-interpreter)
- [How to run untrusted code from an LLM safely](/use-cases/run-untrusted-llm-code)

## Sources

Checked 25 September 2026.

- [Anthropic: code execution tool](https://platform.claude.com/docs/en/agents-and-tools/tool-use/code-execution-tool): how it runs, container limits and pricing
- [OpenAI: Code Interpreter](https://developers.openai.com/api/docs/guides/tools-code-interpreter): container, memory options and expiry

Facts on this page were checked on 25 September 2026.