Gemini API code execution

Overview

Code execution is a built-in tool of the Gemini API (the documentation now lives under AI Studio at aistudio.google.com/docs/code-execution). Passing tools=[{"type": "code_execution"}] lets the model generate Python, run it in a Google-hosted environment and iterate on the result; if the code errors the model may regenerate it up to five times. The environment ships a fixed library set including numpy, pandas, matplotlib, scipy, scikit-learn, sympy, opencv-python, pillow, tensorflow and seaborn, and you cannot install your own. Python is the only language that executes, graphs render with matplotlib only, and the maximum runtime of the environment is 30 seconds.

Input files can be supplied inline or through the Files API (the docs say it works best with text and CSV files) and output files are returned as inline data. Multi-turn use goes through previous_interaction_id; the docs do not say whether interpreter state persists between turns, and do not mention internet access or the isolation technology. Code execution costs nothing beyond the model's standard token rates and can be combined with Grounding with Google Search and, on Gemini 3 and Gemini 4 models, with custom function calling. This is the Gemini API tool; Google's separate Agent Platform code execution service is covered by the google-code-execution record.

Notable

• No additional charge: the docs state "There's no additional charge for enabling code execution"
• Hard limits documented: Python only, 30-second maximum runtime, fixed library list, up to five automatic retries on error
• File input and graph output are documented as available since Gemini 2.0 Flash; image zoom, crop and annotation via code execution is documented for Gemini 3 Flash with Thinking enabled

Gemini API code execution specifications

Facts from Gemini API code execution’s public documentation, verified November 9, 2026. Performance numbers are vendor claims.

Strengths and trade-offs

Strengths

• You want Gemini to check its own maths or produce a chart without paying for or operating a sandbox
• You need a zero-setup option inside an existing Gemini API integration
• You are processing small CSV or text inputs that fit in the model's context window

Trade-offs

• 30-second maximum runtime and Python only, so it is not suitable for builds, long scripts or other languages
• No custom packages, no documented filesystem persistence and no documented network access
• Isolation technology is not documented, so it cannot be assessed for sensitive workloads
• The docs warn that enabling code execution can cause regressions in other outputs, such as creative writing

Good fit for: Calculation, data analysis and chart generation inside a Gemini API call with no sandbox to operate.

Use cases Gemini API code execution fits

• Code interpreters: The Gemini API tool that runs Python for calculation, analysis and charts inside the model call; the isolation technology is not documented.

How Gemini API code execution compares

See all Gemini API code execution alternatives →

Frequently asked questions

Sources

1. aistudio.google.com/docs/code-execution
2. ai.google.dev/gemini-api/docs/code-execution