Meta AI Spreadsheet Reading: formats, limits, features, etc

Meta AI includes the ability to upload files and ask questions about them directly in the chat interface. While official documentation emphasizes media uploads such as images and videos, Meta has also confirmed that users can attach files and receive answers about their content. In late 2025, the platform has not published detailed specifications for spreadsheet formats or size limits, but general patterns indicate that CSV, XLSX, and tabular data inside PDFs or images can be processed with varying effectiveness.

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How Meta AI handles file uploads.

Meta’s help articles explain that users can click Select → Add media or files inside Meta.ai to provide input beyond text. This functionality extends to photos, receipts, and generic file attachments. Once uploaded, users can directly ask Meta AI questions about the file, and the assistant will attempt to interpret the contents.

Although the documentation does not list specific supported document types, the wording makes clear that the assistant is not limited to images and videos. Instead, files can include text-based formats, which suggests spreadsheets in CSV or Excel form are viable inputs, though without guaranteed structured parsing.

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Spreadsheet reading capabilities.

Unlike competitors such as Claude or Gemini, Meta AI has not released a public statement describing native handling of CSV or XLSX spreadsheets. There is no reference to sheet selection, formula evaluation, or structured range addressing. Instead, spreadsheet reading should be understood as a form of text or table extraction from whatever file is provided.

For CSV files, Meta AI can typically interpret the rows and columns as plain text data, enabling summaries, calculations, and pattern detection when prompted explicitly. For XLSX files, results may be less consistent because the format includes binary structures. In such cases, converting to CSV improves compatibility. If data is provided as a PDF or as a screenshot image, Meta AI will attempt to read the embedded table through text or image recognition.

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File size limits and restrictions.

Meta does not publish formal limits for file uploads in its AI chat. This creates uncertainty for spreadsheet use, since large or multi-sheet workbooks may not upload successfully. By comparison, image and video limits are documented, but generic file constraints are absent. In practice, the best approach is to keep file sizes modest and split large datasets into smaller CSV files to avoid upload errors.

The lack of explicit documentation also means that users must rely on experimentation to determine what file sizes are consistently accepted. Enterprise-scale data processing should not rely on Meta AI for spreadsheet uploads until official capacity limits are clarified.

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Prompting strategies for spreadsheets.

Because Meta AI does not offer spreadsheet-specific functions, effective prompting is essential. Users should explicitly reference column names and desired calculations, such as averages, outlier detection, or row sampling. For example, a well-structured prompt might be:

“Analyze the attached CSV. Return a JSON object with the mean, median, and null counts for each column.”

This level of instruction reduces ambiguity and directs the model to treat the uploaded file as structured tabular data. When working with PDFs or images of spreadsheets, prompts should specify which tables or sections to interpret to avoid incomplete responses.

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Workarounds for consistent results.

Practical workarounds help align Meta AI with spreadsheet analysis tasks:

• Convert XLSX to CSV before uploading to ensure clean parsing.

• Use PDF with text layers if data is locked in spreadsheets that need formatting preservation.

• For screenshots or images of spreadsheets, clarify in the prompt that the table is contained in the image and request a structured output format.

• Keep file sizes smaller to minimize risk of rejection.

• Always validate results, since OCR and plain text parsing can introduce errors.

These steps make it more reliable to use Meta AI for spreadsheet reading despite the absence of formal features.

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Table of Meta AI spreadsheet support.

Aspect	Behavior	Notes
Upload mechanism	Add media or files in chat	Works for photos, receipts, generic files
Document formats	Unspecified	CSV and XLSX likely accepted; images and PDFs supported
Spreadsheet features	Not documented	No sheet selection, formulas, or range functions
File size limits	Not published	Keep files small for stability
OCR handling	Supported	Extracts tables from PDFs or images with varying accuracy

This table summarizes the current state of spreadsheet reading in Meta AI and highlights the gaps in published documentation.

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Operational recommendations.

Users seeking to analyze spreadsheets in Meta AI should treat the feature as best-effort file reading rather than structured spreadsheet processing. CSV files are the most reliable format, while Excel workbooks and PDFs with complex layouts may require conversion. Prompts should be explicit, structured, and outcome-driven to guide the model.

Because official support for spreadsheets is not yet formalized, Meta AI is better suited for lightweight or exploratory analysis of tabular data rather than enterprise reporting. Organizations requiring guaranteed parsing and formula evaluation should continue using more specialized AI tools until Meta publishes formal specifications.

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