Which AI is best for multi-tab Google Sheets formulas in FP&A models?

For formulas that reference multiple tabs - SUMIFS from P&L into Returns, FCFF calculations linking Assumptions to Cash Flow - you need an AI that reads your actual file structure. ChatGPT and Claude write syntactically correct formulas but guess at column references and label strings. As of June 2026, Gemini in Workspace reads your active sheet but not inactive tabs. Tools that read your open spreadsheet including all tab structures can identify exact column positions and label text, which is where most multi-tab formula errors originate.

Can ChatGPT write Google Sheets formulas?

Yes, and often well for logic-heavy problems. If you can fully describe your column layout and label strings in text, ChatGPT produces clean formula syntax quickly. The limitation kicks in on multi-tab models: typing out the full schema description for every formula across 8 linked tabs takes longer than it saves. ChatGPT also can't catch label mismatches like "Adj. EBITDA" vs "EBITDA" unless you describe the exact label text, which requires already knowing what's wrong.

Does Gemini work for Google Sheets formulas?

Gemini in Google Workspace reads your active sheet and can write formulas for it directly. Per Google's Workspace product documentation (as of June 2026), formula assistance operates within the currently open sheet. For single-sheet formula problems this works well. For multi-tab models where one formula references P&L, Assumptions, and Balance Sheet simultaneously, Gemini sees only the tab you're on - it can't verify cross-tab column references or row labels on inactive sheets.

Why does a SUMIFS formula return 0 instead of an error?

A SUMIFS returning 0 with no error almost always means the criteria matched nothing in the range. The most common cause in multi-tab models is a label string mismatch - "EBITDA" vs "Adj. EBITDA", or "Revenue" vs "Net Revenue". Per Google's Sheets function documentation, SUMIFS criteria require exact string matches (case-insensitive but length-sensitive) unless you wrap the string in wildcards. To isolate the problem, test each criteria argument separately: `=COUNTIF('P&L'!B:B,"Adj. EBITDA")` tells you immediately whether that label exists in the range. If it returns 0, you have a label mismatch - fix the string before touching anything else.

What's the difference between AI formula tools and Google Sheets' built-in suggestions?

Built-in Sheets features (Smart Fill, formula autocomplete) recognize patterns in adjacent cells and complete predictable sequences. They don't write multi-criteria formulas or handle cross-tab logic. AI tools like ChatGPT go further on complex logic and nested functions but require you to describe your model's structure accurately in text. Context-aware tools that read your open spreadsheet can write formulas against your actual column layout rather than working from a description - which matters most for models where the correct formula depends on what labels and column positions are actually in the file.

Best AI for Google Sheets Formulas (2026 Guide)

That distinction is where most AI formula tools fall apart.

The Context Problem That Breaks AI for Google Sheets Formulas

Here's the failure mode that wastes actual hours.

Your P&L tab uses "Adj. EBITDA" as the row label. Your Returns tab references it with a SUMIFS looking for "EBITDA". The formula is syntactically correct. It returns 0. You paste it into ChatGPT and describe the problem. ChatGPT writes you another SUMIFS with better-looking arguments. Also returns 0.

The root cause: per Google's Sheets function documentation, SUMIFS performs exact string matching on criteria ranges. "Adj. EBITDA" and "EBITDA" are different strings. Without wildcards you get nothing, and without seeing your actual labels, no AI can tell you what string to match against.

That's a contained example. Scale it to a model with 40+ cross-tab references across Assumptions, P&L, Balance Sheet, and Returns tabs, and the same problem compounds at every reference. The AI is writing formulas for a model it cannot see.

Same Prompt, Two Outputs: Building a Multi-Tab SUMIFS Formula With AI

Here's a real problem, sent to two different tools.

The model: 4 tabs (Assumptions, P&L, Balance Sheet, Returns). The P&L tab has period-end dates in column C, row labels in column B (including "Adj. EBITDA" in row 14), and dollar values in column E. The FY2025 period cutoff date sits in Assumptions!$B$3.

The prompt: "Write a SUMIFS formula for my Returns tab that pulls Adjusted EBITDA from the P&L tab for periods on or before the date in Assumptions B3."

ChatGPT (GPT-4o, no file attached):

=SUMIFS('P&L'!C:C,'P&L'!A:A,"EBITDA",'P&L'!B:B,"<="&Assumptions!$B$3)

Three problems the AI couldn't avoid: column C holds dates in this model (values are in E), column A contains nothing useful (labels are in B), and "EBITDA" won't match "Adj. EBITDA". The formula returns 0 with no error to trace. If you don't already know your column layout cold, you're spending 30-45 minutes on something syntactically fine.

ModelMonkey (sidebar reads the open spreadsheet):

The sidebar shows it scanning 'P&L'!B:B and locating "Adj. EBITDA" in row 14. It identifies column E as the numeric value column and column C as the date column from the actual sheet data. The formula it writes:

=SUMIFS('P&L'!$E:$E,'P&L'!$B:$B,"Adj. EBITDA",'P&L'!$C:$C,"<="&Assumptions!$B$3)

Correct columns, exact label match, absolute references for copying down. First try.

The difference isn't intelligence - it's access. ChatGPT would write the same correct formula if you gave it your full column layout in the prompt. The question is whether you want to type out that schema description every time, across every formula, for every tab. For one formula, fine. For building out 40 formulas across a returns model, that process breaks down faster than the model itself.

Where ChatGPT Helps With Google Sheets Formulas

ChatGPT handles pure logic problems cleanly. "How do I use REDUCE to accumulate a running balance while skipping blank cells?" is self-contained - the answer doesn't depend on your file, and ChatGPT produces solid function composition syntax fast.

It's also reliable for formula explanation. Paste a formula you inherited and ask what it does. ChatGPT traces nested IF chains, explains ARRAYFORMULA scope, and flags where edge cases might break things. Useful for auditing models you didn't build.

Translation work is a third strong suit. Converting Excel's XLOOKUP to a Sheets-compatible INDEX/MATCH, or restructuring a SUMPRODUCT to work with FILTER outputs - pattern problems where file contents don't change the answer.

Where it falls apart: any formula where the correct output depends on your actual column headers, row labels, or tab names. That covers most of what you're building in a multi-tab FP&A model.

As of June 2026, Gemini in Google Workspace reads your active sheet. Per Google Workspace's product documentation, Gemini's formula assistance operates within the scope of the currently open sheet. That's better than browser-based AI for single-sheet work, but it loses context the moment your formula references another tab. For a three-statement model where Returns pulls from P&L, Assumptions, and Balance Sheet in a single expression, Gemini sees one of those four sheets at a time.

Honest Limitations Before You Install Anything

No AI formula tool handles every case cleanly.

Context-aware tools that read your open spreadsheet - including tab structure - are more useful for multi-tab work than browser-based AI, but they're not infallible. If you're running iterative calculation for circular reference models (three-statement models with a revolver, for instance), verify output carefully before it goes anywhere near investors. The formula might be syntactically correct and still resolve wrong if the iteration sequence matters.

ChatGPT with a file attached (ChatGPT Plus, as of mid-2026) can read spreadsheet contents from an uploaded XLSX, which narrows the context gap. The limitation: formulas and cross-tab links don't survive XLSX upload intact. You're giving the AI flat data, not a live model.

The right frame regardless of tool: use AI to draft formulas faster. Use your own verification pass to confirm they work. Your boss notices when the P&L EBITDA figure doesn't tie to the Returns tab, and that's your name on the model.

Try ModelMonkey free for 14 days - it works in both Google Sheets and Excel.