Can Gemma 4 Replace ChatGPT for Spreadsheet Analysis?

Gemma 4 can replace ChatGPT for some spreadsheet help—such as explaining a formula, drafting a SUMIFS, or proposing a data-cleaning approach—but not as a direct feature-for-feature substitute. ChatGPT includes spreadsheet upload, code execution, tables, charts, and spreadsheet-native integrations. A locally downloaded Gemma 4 model needs a separate application, parser, and usually a safe code-execution tool before it can inspect or transform an actual workbook.

The right comparison is therefore not simply “Gemma 4 versus a ChatGPT model.” It is your complete local Gemma workflow versus ChatGPT's data-analysis workflow, tested on the same files and acceptance criteria.

Correcting the original test setup

The original article claimed to test a “27-billion-parameter Gemma 4” in Ollama against GPT-4o, then presented conclusions without files, complete outputs, workbook versions, or reproducible scoring. Google does not list a 27B Gemma 4 model. The official Gemma 4 family currently includes E2B, E4B, 12B, 26B A4B, and 31B variants.

That makes the quoted results unreliable. They should not be used to conclude that a model “won,” that a VBA macro ran successfully, or that an answer was production-ready. This revised comparison focuses on verifiable product capabilities and a test method readers can repeat.

Gemma 4 and ChatGPT: capability comparison

Spreadsheet task	ChatGPT	Local Gemma 4
Open XLS/XLSX/CSV	Supports common spreadsheet uploads in data analysis; availability depends on plan and workspace settings.	The model alone cannot open a file. The local app must parse it and provide the relevant contents.
Run calculations	Can run code in a secure analysis environment and show the work.	Needs a separate tool or sandbox. Without one, it only proposes formulas or code.
Create charts	Can generate supported charts from uploaded data and offer downloads.	Can suggest chart types or write plotting code; another program must execute and render it.
Edit a workbook	ChatGPT for Excel and Google Sheets can work in the spreadsheet when available; ordinary file analysis can also create transformed outputs.	Requires a local integration that can safely write workbook files while preserving formulas and formatting.
Work offline	Generally requires the service and network connection.	Possible when the model, runtime, parser, and tools all run locally.
Current Excel knowledge	Can use web or connected features when enabled, but generated guidance still needs verification.	Limited to training knowledge and supplied documentation unless a search tool is added.
Data governance	Depends on account type, workspace controls, connected sources, and current data policies.	Can keep data on-device only if every component is local and telemetry or network tools are disabled.

Where Gemma 4 can be enough

A local Gemma model can be practical when the task is text-based and narrowly defined:

• explain why a formula returns an error;
• draft a formula from a clearly described table layout;
• convert an Excel formula to an equivalent Google Sheets expression;
• suggest a Power Query sequence or VBA outline;
• review a small, anonymized CSV excerpt pasted into the prompt;
• brainstorm validation rules or chart choices.

The model size matters. Google's smaller E2B and E4B variants prioritize on-device deployment, while the 12B and larger variants need more capable hardware. A quantized model uses less memory but can behave differently from the full-precision version. Record the exact model, quantization, runtime, system prompt, and context settings whenever you compare results.

Where ChatGPT has a workflow advantage

ChatGPT's data-analysis capability can read common spreadsheet files, run Python code, inspect intermediate tables, calculate results, and create charts. OpenAI also offers ChatGPT inside Excel and Google Sheets, subject to current account and workspace availability.

That tool access matters more than a polished text answer. A formula suggested in chat is only a hypothesis; a formula inserted into a copied workbook and recalculated against test cases provides evidence. ChatGPT can still make mistakes, misread headers, choose an unsuitable date interpretation, or alter workbook structure, so the result must be audited.

See OpenAI's current data analysis documentation and spreadsheet integration guide for supported workflows.

Test 1: cleaning mixed dates safely

The original prompt asks for one formula to normalize dates that mix dd/mm/yyyy, mm-dd-yyyy, yyyy.mm.dd, and written dates. That is unsafe without a locale rule: 03/04/2025 could mean 3 April or March 4, and no formula can infer the intended meaning from that value alone.

A better prompt is:

The Date column contains four declared formats:
1. dd/mm/yyyy with slash
2. mm-dd-yyyy with hyphen
3. yyyy.mm.dd with periods
4. English written dates such as 15 March 2025

Treat ambiguous slash dates as day-first. Do not guess if a value violates its declared pattern. Produce:
- a Power Query approach,
- an Excel 365 helper-column formula,
- an ErrorReason column,
- five edge-case tests.
Do not overwrite the source column.

Both models should be judged on whether they preserve true Excel date values, flag impossible dates, state locale assumptions, and avoid formatting a text error as if it were a valid date. For recurring imports, Power Query is usually easier to audit than one deeply nested formula.

Test 2: PivotTable and formula summary

For a table named Sales with columns Region, Category, and Revenue, a formula-based matrix can use:

=SUMIFS(Sales[Revenue],Sales[Region],$A2,Sales[Category],B$1)

A good answer should explain the mixed references, ensure the headers match the source categories, handle new rows through the Excel Table, and distinguish a recalculating formula matrix from a PivotTable that may require refresh. Suggestions such as conditional formatting are optional; they do not compensate for an incorrect formula.

Test 3: merging worksheets with VBA

AI-generated VBA should never be labeled production-ready merely because it looks plausible. A reliable consolidation macro needs explicit decisions about:

• which sheets to include and how the Summary sheet is identified;
• whether every source has headers and the same columns;
• what to do with empty sheets and formula errors;
• whether to copy values, formulas, formats, or all three;
• how to preserve or clear existing Summary data;
• how application state is restored after an error;
• how many source rows were expected and copied.

On Error Resume Next is not automatically “robust”; it can silently hide failed operations. Prefer narrow error handling, a cleanup block that restores ScreenUpdating and calculation state, and a copied workbook with test sheets for empty, malformed, and maximum-size cases.

Test 4: chart recommendations

Both systems can recommend a line chart for a time trend, grouped bars for category comparison, or a combination chart when two measures use compatible storytelling. The useful answer also checks whether a second axis could mislead, whether categories are too numerous, how missing months are represented, and what decision the audience needs to make.

Do not award points for suggesting more chart types. Ask each system to justify one primary chart, specify the aggregation, and produce an underlying summary table that can be checked independently. Avoid 3D charts because visual perspective distorts comparison.

Test 5: debugging a formula

Consider this formula:

=IFERROR(VLOOKUP(A2,Sheet2!B:F,5,TRUE),"Not Found")+IF(C2>"100",D2*0.1,D2*0.05)

The original article says wrapping the whole expression in IFERROR is necessarily better. That depends on the intended output: adding the text "Not Found" to a number already creates a value error. The business rule must be clarified before rewriting.

Likely problems include:

• TRUE requests an approximate match and requires sorted lookup data; an exact identifier lookup normally uses FALSE.
• "100" is text, while 100 is numeric.
• The formula combines a lookup result and a percentage calculation without stating what should happen when the lookup is missing.
• A broad IFERROR can hide unrelated data-quality problems.

For an exact numeric lookup where a missing record should return a label instead of a total, a clearer Excel 365 structure might be:

=LET(
  found,XLOOKUP(A2,Sheet2!B:B,Sheet2!F:F,NA(),0),
  bonus,IF(C2>100,D2*10%,D2*5%),
  IF(ISNA(found),"Not Found",found+bonus)
)

Verify the lookup column and return column against the actual workbook before using this example.

Privacy: local does not automatically mean private

Running Gemma 4 on your own hardware can keep spreadsheet content off a cloud AI service, but only if the entire workflow remains local. A desktop chat app may send telemetry, fetch remote models, call web search, or pass code to another service. Inspect its settings, network behavior, plug-ins, logs, and storage.

Conversely, “cloud” does not describe one universal ChatGPT data policy. Consumer, Business, Enterprise, Edu, and API products can have different controls, retention, and administrative settings. Follow your organization's data classification and approved-tool policy rather than uploading a sensitive workbook based on a general assumption.

For either system, remove unnecessary personal data, use a representative copy, protect formulas and source files, and never include credentials or access tokens in cells or prompts.

A reproducible comparison method

1. Create a sanitized workbook with known answers and a separate untouched baseline.
2. Define acceptance tests for formulas, row counts, totals, dates, blank cells, duplicates, and error cases.
3. Record the exact model and tool configuration.
4. Give each system the same task and the same permitted tools.
5. Save complete prompts, outputs, generated code, and execution logs.
6. Recalculate the workbook in Excel or the target spreadsheet application.
7. Compare correct results, hidden errors, review time, data exposure, hardware cost, and service cost.

Verdict

Gemma 4 can be a capable offline assistant for formulas, explanations, and code drafts, particularly when privacy requirements justify a carefully controlled local setup. ChatGPT is the more complete out-of-the-box spreadsheet analysis environment because it can work with files, execute calculations, create charts, and operate inside spreadsheets.

Neither should be trusted by reputation or a one-off prompt. Choose the workflow that passes your workbook's tests, fits your governance requirements, and leaves a human able to trace every important number back to the source.