E2B vs OpenSandbox: a hosted sandbox API against a control plane you run

A hosted API against a control plane you start yourself

Both projects solve the same problem, running code you do not trust inside an isolated environment, and both are Apache-2.0 licensed, so the licence is not what separates them. The difference is where the sandbox lives and who runs it. E2B presents itself as infrastructure you call over a network. You install an SDK, set an API key, and create a sandbox that lives in E2B's cloud, while the same project also publishes the infrastructure for running it on your own account. OpenSandbox presents itself as a runtime with a control plane. You start a server, and it manages sandboxes on Docker locally or on Kubernetes at scale, and it defines a protocol so other languages and tools can drive the same sandboxes. The dividing line in practice is the API key and the bill. E2B assumes a remote dependency by default. OpenSandbox assumes a server process you launch.

E2B is a hosted product with an open infrastructure layer

E2B's surface is small. The README's first script creates a sandbox, runs a shell command in it and prints the standard output, and the same flow exists for Python and JavaScript. Two optional SDKs sit on top of that base. A code interpreter, exposed as `runCode()` and `run_code()`, executes code rather than shell commands, and a desktop SDK can launch an application and take a screenshot, which is what a computer-use agent needs. The infrastructure half is where the open-source part carries weight. The README's self-hosting section points at a separate guide, states that the infrastructure is deployed with Terraform, and lists AWS and Google Cloud as supported while Azure and a general Linux machine remain unchecked. Our analysis of E2B draws the line the same way: take it if you need to execute untrusted code or control a desktop, and leave it if Azure support, a plain Linux host or a fully local sandbox without an external API key is a requirement.

OpenSandbox is a protocol with a server, a CLI and many SDKs

OpenSandbox's architecture is wider. The README describes three layers: SDKs, a CLI and an MCP server for sandbox creation, command execution and file operations; a Sandbox Protocol that specifies lifecycle and execution APIs so custom sandbox runtimes can be written; and a Sandbox Runtime that handles lifecycle management over Docker and a high-performance Kubernetes runtime. On top of that sit built-in Command, Filesystem and Code Interpreter environments, with examples covering coding agents, browser automation and desktop use. Two features matter most to a team running model-generated code. A credential vault injects secrets into outbound requests without giving the real values to the workload, and per-sandbox egress controls sit behind a unified ingress gateway. The isolation options are named too, with gVisor, Kata Containers and Firecracker microVMs listed as supported secure container runtimes.

Getting each one running for the first time

The E2B path is the shorter one. Install the SDK with pip or npm, export `E2B_API_KEY`, and the first script creates a sandbox and runs a command in it. Self-hosting E2B is a different job, involving Terraform, a cloud account and the infrastructure repository. The OpenSandbox path starts local but asks for more setup decisions. The README lists Docker as required for local execution and Python 3.10 or newer, and the server is started with `uvx opensandbox-server` after `uvx opensandbox-server init-config ~/.sandbox.toml --example docker`. The CLI is configured the same way for everyone, with `osb config set connection.domain localhost:8080`, and the code interpreter arrives as a package of its own. The protocol is the reason a non-Python team can join: SDKs exist for Java, Kotlin, C#, Go and TypeScript beside Python, and the `osb` command line tool drives the same server.

What each one costs to operate afterwards

E2B's operating cost has two parts. The hosted path puts a network round trip in front of every command and every screenshot, so our analysis of E2B calls latency and data egress the real test, and says to prototype with a simple script before scaling, after checking the documented timeout limits, sandbox persistence and what long-running sessions cost you. The self-hosted path replaces that with a Terraform deployment on AWS or GCP that somebody has to own. OpenSandbox's operating cost is the server and the cluster behind it. Its published creation latency is 97 ms at the 50th percentile, and the README states the conditions in a footnote: template artifacts cached, a reference host, and a measurement taken over 100 creates, so cold starts are not inside that number. Scaling means Kubernetes, and scheduling and node capacity become your problem to solve.

Same Apache-2.0 licence, different maturity signals

Both projects carry Apache-2.0, which allows commercial use and asks you to preserve notices when you redistribute. That is the one place where they do not differ. Their maturity signals differ. The last push to E2B was on 2026-10-21, and its SDK release line stood at 2.49.0 in September 2026. The last push to OpenSandbox was on 2026-10-21 as well, but its components are versioned on separate lines: python/sandbox at v0.1.16, server at v0.2.3 and docker/execd at v1.1.0, all published on the same day in August 2026. A component versioned independently is also a component you have to pin on its own. OpenSandbox says so itself: release images are signed keylessly with Cosign, carry provenance attestations, and should be pinned by digest in production.

Where each choice is the weaker one

OpenSandbox is the weaker choice for a team that wants a sandbox in a few lines of Python and does not want to own a server, a Docker daemon or a Kubernetes cluster. Its README points at components still on 0.x lines, and our analysis of OpenSandbox advises pinning the SDK deliberately for exactly that reason. E2B is the weaker choice when the environment cannot reach the internet, when the provider you use is Azure, or when you cannot accept a network hop in front of every shell command. It is also the weaker choice for a team that would rather run one runtime across a mixed fleet of laptops and servers, because the self-hosting path assumes Terraform and a supported cloud. The tie-breaker is usually about who runs the control plane. If the answer is one person with a cloud account, E2B is the shorter road, and if the answer is a platform team, OpenSandbox hands them more to work with.

Bottom line

If one person can hold a cloud account and an API key, start with E2B and check the timeout limits before long sessions run. If a platform team will own a control plane, take OpenSandbox, pin the python/sandbox version you use, and measure cold starts on your own nodes. The deciding question is whether you can accept a network hop for every command.

Sources

1. e2b-dev/E2B repository
2. e2b-dev/E2B README
3. opensandbox-group/OpenSandbox repository
4. opensandbox-group/OpenSandbox README