What is the best alternative to OpenAI Code Interpreter?
It depends on how long a session lives and which model drives it. For sessions that mostly wait on a model, Runtime runs a 20-minute, 4 GiB session for at most $0.0267, below the price of OpenAI's 4 GB container. It supports any model's code, your own image, and a session that survives a long pause. Keep Code Interpreter for quick Python answers inside an OpenAI conversation, when a 20-minute session and the container's packages cover the job.
What Code Interpreter is
Code Interpreter is a built-in tool of OpenAI's Responses API. In OpenAI's words, it "allows models to write and run Python code in a sandboxed environment", and "the model knows it as the 'python tool'".
- Containers. The tool runs in a container. With
"type": "auto", OpenAI creates one. You can also create one yourself at/v1/containersand pass its id. - Memory.
1g(the default),4g,16gor64g. OpenAI's guide and pricing name memory tiers, not CPU counts. - Lifetime. "A container expires if it is not used for 20 minutes." Its data is then "discarded from our systems and not recoverable".
- Files. Files in the model input are uploaded to the container for you. Files the model creates come back as annotations on its message.
- Network. A container created through the API takes a
network_policy: outbound access disabled, or an allowlist of domains, with optional domain-scoped secrets.
What it costs
OpenAI's price list, checked 26 October 2026: "1 GB $0.03, 4 GB $0.12, 16 GB $0.48, 64 GB $1.92 per 20-minute session per container." Its footnote adds that "eligible container sessions will be billed by the minute, with a 5-minute minimum per session." Tokens are billed on top, at the model's rates.
The same sessions on Runtime, at 2 vCPU and 4 GiB, cost $0.03125 an hour while the code waits and $0.08 an hour with both CPUs busy:
| Session | OpenAI, 4 GB container | Runtime, 2 vCPU and 4 GiB |
|---|---|---|
| 20 minutes, mostly waiting | $0.12 | 20 / 60 × $0.03125 = $0.0104 |
| 20 minutes, both CPUs busy | $0.12 | 20 / 60 × $0.08 = $0.0267 |
| One minute, where per-minute applies | 5-minute minimum: 5 / 20 × $0.12 = $0.03 | 1 / 60 × $0.08 = $0.0013 at most |
| 1,000 sessions of 20 minutes | $120.00 | $10.42 waiting, $26.67 busy |
Model tokens are left out of both columns. Runtime has no minimum charge per session (pricing).
Where your own sandbox does more
| Need | OpenAI Code Interpreter | Runtime sandbox |
|---|---|---|
| Model | OpenAI models, through the Responses API | Any model or framework; your code calls the sandbox |
| Languages in the notebook | Python, "the python tool" | Python, JavaScript, TypeScript, R, Java, Bash and Go |
| The machine | OpenAI's container. A create sets memory, files, network and skills | Your image: a package recipe, any public or private image, or a Dockerfile |
| An idle session | Expires after 20 minutes unused, and its data is discarded | Pauses with files, memory and processes, kept while you have credit |
| Copies of a session | None in OpenAI's guide | Fork 1 to 100 running copies, memory included |
| Isolation | "A sandboxed environment" | A Firecracker microVM with its own Linux kernel |
| Billing | Memory tier, per 20-minute session | Measured CPU plus reserved memory while running, with no minimum |
The interpreter keeps variables between cells. Charts come back as PNG, and data frames come back as tables (code interpreter). Network rules apply to root inside the sandbox too, because the host enforces them (security).
Which one fits
- Keep Code Interpreter for quick Python answers inside an OpenAI conversation, when a 20-minute session and the container's own packages cover the job.
- Use your own sandbox when the code needs packages or tools you choose, a language other than Python, a session that survives a long pause, a model from more than one provider, or a bill that follows the CPU used.
Runtime Cloud
Runtime runs the same 20-minute, 4 GiB session for $0.0104 to $0.0267, against $0.12 for OpenAI's 4 GB container. Runtime bills the CPU the code uses and the memory it holds, so a session that mostly waits for the model costs little. OpenAI prices every container by its memory tier for each 20-minute session. OpenAI rates checked 25 October 2026; Runtime's are in pricing.
Try it without credit:
Terminalprintf '%s\n' 'print(sum([125, 250, 375]))' > invoice.pynpx withruntime sandboxes run -- python3 - < invoice.pyThe first run prints a link to approve in your browser. There is no API key to copy.
More: add a code interpreter to a chatbot, what is a code interpreter?, data analysis agent, Claude code execution tool alternative.
Once that first run works, Get started adds the SDKs. The migration guide moves code from another sandbox provider.
The Runtime equivalent
Install what the model needs, close the network, then run its cells. The sandbox pauses itself after ten quiet minutes and wakes on the next cell:
TypeScriptimport { Sandbox } from "withruntime";await using sbx = await Sandbox.create({ network: { internet: true, allow: ["pypi.org", "*.pythonhosted.org"] }, idlePauseSeconds: 600,});await sbx.exec("pip install --quiet scikit-learn", { check: true, timeoutMs: 300_000 });await sbx.network.set({ internet: false }); // nothing leaves while the model's code runsawait sbx.interpreter.run( "from sklearn.datasets import load_iris\nX, y = load_iris(return_X_y=True)",);const cell = await sbx.interpreter.run("X.shape");console.log(cell.results[0]?.data["text/plain"]); // (150, 4)Pythonfrom withruntime import Sandboxwith Sandbox.create( network={"internet": True, "allow": ["pypi.org", "*.pythonhosted.org"]}, idle_pause_seconds=600,) as sbx: sbx.exec("pip install --quiet scikit-learn", check=True, timeout_ms=300_000) sbx.network.set(internet=False) # nothing leaves while the model's code runs sbx.interpreter.run("from sklearn.datasets import load_iris\nX, y = load_iris(return_X_y=True)") cell = sbx.interpreter.run("X.shape") print(cell["results"][0]["data"]["text/plain"]) # (150, 4)Expose a function like this to the model as a tool, and return the cell's
output as the tool result. With the OpenAI Agents SDK, RuntimeCloudSandboxClient
runs a SandboxAgent's shell and files in a Runtime sandbox, with the agent
unchanged (OpenAI Agents SDK).
Sources
Checked 26 October 2026.
- OpenAI: Code Interpreter guide
- OpenAI: API pricing
- OpenAI: containers API reference
- Runtime pricing, JavaScript SDK and Python SDK
Facts on this page were checked on 26 October 2026.