Best sandbox for CrewAI in 2027

Q: Which sandbox service should a crew use?

What decides it for a crew: One machine or many. Agents in a crew hand work to each other. If they share one sandbox, the researcher's downloaded data is where the analyst reads it. If each has its own, a mistake by one never touches another's files. No wrapper to maintain. Functions with type hints and docstrings become CrewAI tools through tool(f) from crewai.tools, with nothing in between. A real environment. An engineer agent fixing tests needs the project's toolchain: git, a compiler, Python and often Docker. A machine that waits cheaply. Crews idle between steps. A sandbox that pauses when nothing happens and resumes on the next tool call costs little while the agents talk.

Q: When might another sandbox fit better?

GPU steps. A crew that fine-tunes or serves a model on a GPU fits Modal, one of the two services CrewAI names.

Which sandbox is best for CrewAI?

It depends on whether a crew needs a GPU. Crews spend most of a run with agents talking to each other and the model. For that work, Runtime is the lower-cost option: $16.88 for three thousand ten-minute runs, compared with $82.80 on E2B and $118.98 on Modal, the two services CrewAI names. Runtime bills measured CPU use and gives agents a full Linux machine through CrewAI's own tool. Pick Modal if a step fine-tunes or serves a model on a GPU.

What happened to code execution in CrewAI?

CrewAI's CodeInterpreterTool page, read on 25 October 2026, says the tool "has been removed from crewai-tools", that "the allow_code_execution and code_execution_mode parameters on Agent are also deprecated", and to "use a dedicated sandbox service — E2B or Modal — for secure, isolated code execution".

So a crew that runs code now needs a sandbox and a way to call it. CrewAI already turns any typed function into a tool, which is all a sandbox needs.

Which sandbox service should a crew use?

Service	Isolation	What a crew agent gets	CPU billed on
Runtime Cloud	Firecracker microVM	A shell, files, `pip`, `sudo`, Docker	Measured use
E2B	Firecracker microVM	E2B's code interpreter and sandbox SDK	Every vCPU held
Modal	gVisor, a shared kernel	Modal's sandbox API, inside a Modal App	The CPU requested

What decides it for a crew:

One machine or many. Agents in a crew hand work to each other. If they share one sandbox, the researcher's downloaded data is where the analyst reads it. If each has its own, a mistake by one never touches another's files.
No wrapper to maintain. Functions with type hints and docstrings become CrewAI tools through tool(f) from crewai.tools, with nothing in between.
A real environment. An engineer agent fixing tests needs the project's toolchain: git, a compiler, Python and often Docker.
A machine that waits cheaply. Crews idle between steps. A sandbox that pauses when nothing happens and resumes on the next tool call costs little while the agents talk.

What does a month of crew runs cost?

Three thousand runs, each ten minutes on a 2 vCPU, 4 GiB sandbox and busy for 90 CPU-seconds, at the published rates of the two services CrewAI names and of Runtime:

Provider	A month of crew runs	Runtime costs less by
Runtime Cloud	$16.88
E2B	$82.80	80%
Modal	$118.98	86%

When might another sandbox fit better?

GPU steps. A crew that fine-tunes or serves a model on a GPU fits Modal, one of the two services CrewAI names.

Runtime Cloud

Runtime gives a crew a Linux microVM per task, or one shared machine for the whole crew, through four typed functions that CrewAI's tool wraps as they are. Each command runs in a Firecracker microVM with its own kernel, where pip install, git and gcc work. The default image already has git 2.43, gcc 13 and Python 3.12. Docker starts with sudo enable-docker. A sandbox with nothing happening pauses itself after 300 seconds and resumes on the next tool call.

Crews spend most of their time with agents talking to each other and the model. Runtime bills that time at its CPU floor of a twentieth of a vCPU per vCPU. The three thousand crew runs above cost $16.88 on Runtime, 80% less than E2B and 86% less than Modal, at rates checked 25 October 2026. Runtime runs on CPUs only.

A run on Runtime, recorded 2 October 2026

Pythonfrom crewai import Agent, Crew, Taskfrom crewai.tools import toolfrom withruntime import Sandboxfrom withruntime.tools import sandbox_toolswith Sandbox.create() as sbx:    engineer = Agent(        role="Engineer",        goal="Make the test suite pass",        backstory="You work in a Linux sandbox.",        tools=[tool(f) for f in sandbox_tools(sbx)],    )    task = Task(description="Clone the repo, run the tests and fix what fails.", expected_output="A summary", agent=engineer)    print(Crew(agents=[engineer], tasks=[task]).kickoff())

A crew's kickoff needs a real model. So on 2 October 2026 we called the wrapped runtime_exec tool through CrewAI's own tool object, as an agent does, against a live sandbox:

textruntime_exec "git --version && gcc --version | head -1 && python3 --version"  exit_code 0  git version 2.43.0  gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0  Python 3.12.3

Several agents sharing one sandbox, and the safety settings for a crew, are in CrewAI in a sandbox.

A crew can try this on free usage once you run npx withruntime login. Tools already written for E2B or Modal switch over with the migration guide.

Sources

Checked 25 October 2026.

CrewAI CodeInterpreterTool: the removal notice, the deprecated Agent parameters and the sandbox services it names
Each provider's published rates, checked 25 October 2026, as the pricing guide lists them
The recorded run: Runtime's Python SDK with CrewAI's tool from crewai 1.15.23 on Python 3.12, against production on 2 October 2026