ChatGPT, Gemini, Claude for spreadsheets: full comparison of features, uploads, and automations (2025)

AI chatbots can now read, edit, and generate spreadsheets directly in chat.

Chat-based AI tools are no longer limited to answering questions or generating texts. Today, they are increasingly used for working with data, analyzing spreadsheets, generating pivot tables, creating charts, and even automating reporting tasks. Whether you're dealing with CSV exports, Excel financial statements, or raw logs, ChatGPT, Gemini, and Claude can all process them—but with different levels of capability and integration.

In this article, we break down the latest spreadsheet features of these three AI assistants as of mid-2025 and beyond, including file upload support, data analysis, integrations with cloud storage, and practical use cases.

ChatGPT supports spreadsheet analysis with real Python code execution.

The most advanced file handling among AI chatbots is currently offered by ChatGPT, especially in the GPT-4o and o-series versions available to Plus and Pro users. The system allows users to upload XLS, XLSX, and CSV files up to 512 MB each, and interact with them in a Python-powered environment capable of generating real analyses, tables, and plots.

The interface shows tabular previews after upload and allows asking natural questions such as: “Which products had the highest margin in Q2?” or “Create a pie chart of expenses grouped by category.” These operations are executed using real Python libraries like pandas and matplotlib, with full visibility of the results.

In addition, Pro users can now rely on ChatGPT Agent, which goes beyond chat prompts and autonomously creates new spreadsheets, fills templates, and extracts data from files to populate external systems like CRMs or databases. File exports (e.g., into .xlsx format) can also be requested directly in conversation.

The assistant supports up to 20 files per chat (40 in “Projects”), and integrates natively with Google Drive, OneDrive, SharePoint, Dropbox, and mobile file systems. The maximum token context of 128,000 tokens ensures support for large datasets and long-running analysis.

Gemini is tightly integrated into Google Sheets and works both inside and outside chat.

Gemini, developed by Google, offers spreadsheet processing in two ways: directly in Google Sheets or through the Gemini web interface. Both paths offer useful features, but with different focuses.

Inside Sheets, users can open the “Ask Gemini” side panel, which reads selected ranges and allows natural-language prompts such as: “Summarize this table,” “Format this as a pivot,” or “Add conditional formatting by revenue.” A unique feature is the =AI() function, which can be typed directly into a cell to generate text, summaries, or categorization based on other cells’ content. This is extremely useful for repetitive tasks such as tagging entries, translating rows, or analyzing sentiments.

Outside Sheets, users can upload up to 10 spreadsheet files (100 MB each) into gemini.google.com and interact through prompts like: “Generate a bar chart of total revenue by region.” Gemini then returns a visualization or summary ready for copy-pasting into reports or slides. On the Pro and Ultra plans, the model uses a 1 million token context window, the largest among the three platforms, allowing for deep document understanding across multiple sheets or files.

However, Gemini’s cell-level operations are limited to one range at a time, and large or complex datasets may produce inconsistent outputs. It does not support code execution or direct scripting within Gemini itself but can be paired with AppSheet or Apps Script for more advanced workflows.

Claude processes large spreadsheets and supports in-cell automation at scale.

Claude, developed by Anthropic, allows users to upload spreadsheets (CSV, XLSX) both via chat interface and the Files API. The Opus 4 model, available to Claude Pro or Max users, supports a context window of 200,000 tokens, which enables it to work with extended datasets and multi-tab Excel files in one go.

Although Claude does not run code like ChatGPT, it excels at summarizing tables, answering questions about structure, detecting outliers, and extracting specific patterns from spreadsheets. It handles up to 20 files per chat, with each file maxing out at 30 MB via chat or 500 MB via API.

A key feature for enterprise users is the Claude for Sheets add-on. After configuring it with an Anthropic API key, users can deploy the =CLAUDE() function across entire columns or ranges to perform tasks such as mass translation, prompt-based row generation, or bulk classification—all directly in Google Sheets.

Unlike ChatGPT, Claude doesn’t preview uploaded spreadsheets in the chat UI, and complex files may occasionally time out. However, when paired with the Files API, Claude can be used in scheduled pipelines, reading spreadsheet data, generating analysis, and returning outputs as text or downloadable CSVs on a recurring basis.

Summary of differences in spreadsheet capabilities

Feature	ChatGPT	Google Gemini	Claude
Upload support	CSV, XLS, XLSX (512 MB)	CSV, XLSX, Google Sheets (100 MB)	CSV, XLSX (30 MB via chat, 500 MB via API)
Analysis engine	Python sandbox + graphs	Gemini-native engine + chart builder	LLM-only, no code execution
Cloud integrations	Drive, OneDrive, Dropbox	Native in Google Sheets	Google Sheets via add-on
In-cell functions	❌	=AI()	=CLAUDE()
Context window	128k tokens	1M tokens (Pro)	200k tokens (Opus 4)
Automation	ChatGPT Agent for workflows	Google Apps Script, AppSheet	Claude API workflows

Which one should you choose for spreadsheet tasks?

If your needs involve data manipulation, real statistical analysis, and chart creation, ChatGPT with GPT-4o or o3 is the most versatile option thanks to its integrated Python environment. It also supports native automation with ChatGPT Agents.

If your workflow revolves around Google Sheets, Gemini provides the most seamless experience, with native sidebar integration and =AI() functions that simplify repetitive tasks.

Claude, on the other hand, is ideal for scalable operations in bulk, especially if you want to use prompts directly on thousands of rows inside Google Sheets, or if you're dealing with very large datasets that exceed other models' context limits.

Each tool offers unique advantages depending on how you use spreadsheets—whether for interactive analytics, enterprise-scale classification, or embedded automation.

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