Gemini

Gemini Code Execution Error — Fix

Gemini's built-in code execution sandbox allows Python code to run directly inside the model, but users sometimes encounter errors where code fails silently, throws exceptions, or simply does not execute at all. This issue is commonly seen by developers and analysts using Gemini for data processing, calculations, or automated scripting tasks. Understanding the sandbox's limitations and configuration requirements is the fastest path to resolving this error.

Why does this error happen?

Gemini's code execution feature runs Python in an isolated, resource-constrained sandbox environment that is separate from your local machine or any external runtime. The sandbox only supports specific Python libraries, enforces strict execution time limits, and must be explicitly enabled in the model's configuration before it can run any code. Errors occur when the feature is disabled, when an unsupported or unavailable library is imported, when the code exceeds complexity or memory thresholds, or when the request is made using an older model version that does not support code execution at all. Additionally, large monolithic scripts can exceed sandbox resource limits, causing incomplete or failed execution without a clear error message.

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How to fix it

Enable Code Execution in Model Settings

Code execution is not active by default in all Gemini configurations. Navigate to your Gemini API settings or the Google AI Studio interface and confirm that the code execution tool is toggled on before sending your request. If you are using the API directly, ensure the 'code_execution' tool is included in your tools array when constructing the model request.

Upgrade to Gemini 1.5 Pro or Newer

Code execution is only supported on Gemini 1.5 Pro and later model versions, including Gemini 1.5 Flash and Gemini 2.0 models. If you are on an earlier model version, the sandbox will not be available and your code will not run. Check your current model selection in the API request or the AI Studio model picker and switch to a supported version.

Verify That Required Libraries Are Available

Gemini's sandbox includes a pre-approved set of Python libraries such as NumPy, Pandas, Matplotlib, and a handful of other common packages. If your code imports a library that is not available in the sandbox, execution will fail with an import error. Review your import statements and replace unsupported libraries with sandbox-compatible alternatives, or restructure the logic to avoid external dependencies.

Break Complex Code Into Smaller Executable Chunks

Large or deeply nested scripts can exceed the sandbox's memory and execution time limits, causing failures that are difficult to diagnose. Split your code into smaller, self-contained logical blocks and test each segment individually within the conversation. This approach also makes it easier to identify exactly which portion of the code triggers the error.

Pro tip

Always prototype your sandbox code with minimal dependencies and a small dataset first — confirm execution succeeds before scaling up to larger inputs or adding additional library imports, since sandbox resource limits are non-negotiable and will silently terminate overloaded scripts.

Frequently asked questions

Which Python libraries are supported in Gemini's code execution sandbox?

Gemini's sandbox supports a curated set of popular libraries including NumPy, Pandas, Matplotlib, SciPy, and several other standard scientific computing packages. You can find the full current list in Google's official Gemini API documentation, as supported libraries may expand with model updates.

Can Gemini access the internet or external files during code execution?

No, the Gemini code execution sandbox is completely isolated and does not have access to the internet, external APIs, or your local file system. All data used during execution must be provided directly within the prompt or generated by the code itself.

Why does Gemini sometimes return a result without actually running the code?

If code execution is not enabled or the model version does not support it, Gemini will simulate a response by reasoning about what the code would produce rather than executing it. Always verify the response includes a code execution output block to confirm the code genuinely ran in the sandbox.

Is there a timeout limit for code execution in Gemini?

Yes, the sandbox enforces a hard execution time limit to prevent runaway scripts from consuming resources. If your code runs longer than the allowed threshold, it will be terminated mid-execution, so optimizing for speed and breaking tasks into smaller chunks is strongly recommended.

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