Finance AI Index
Index Planning and analysis Financial modeling › Datarails vs Microsoft Excel
Financial modeling and scenario planning · September 2026 Edition

Datarails vs Microsoft Excel

Eight of twelve models named Datarails first on the direct prompt; zero named Microsoft Excel. Datarails was named by eleven of the twelve models and Microsoft Excel by eight and Datarails carries 21 labels and Microsoft Excel 14, so the shares are not directly comparable.

Datarails

accepted challenger

Named in ten categories this edition.

Microsoft Excel

accepted challenger

Named in eleven categories this edition.

First-choice share19%11%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%21%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 8; printed, not drawn.
Labels2114A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Datarails reading right to left. Rank and label count are printed, not drawn.Cube was named alongside these two in nine of the twelve direct answers. Datarails vs Google Sheets · Datarails vs Cube · Datarails vs Vena

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the financial modeling and scenario planning page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
DatarailsFirst choices, of twelve modelsMicrosoft Excel
Direct80
Paraphrase001 against Microsoft Excel
Comparative01
Budget-constrained051 against Datarails
Scale-constrained10
Negative002 against Microsoft Excel
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Datarails and Microsoft Excel stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Datarails Microsoft Excel first choice named as an alternative argued againstblank: not namedEach cell is one answer, Datarails on the left and Microsoft Excel on the right.

The direct prompt

The plain question, one answer per model, grouped by where Datarails and Microsoft Excel stood in it.

Datarails first, Microsoft Excel not the choice

8 of 12 modelsMicrosoft Excel was named in the answer but not as the choice, or not at all.
GPT-5.4 miniDatarails alternatives: Abacum, Anaplan
Perplexity SonarDatarails, Drivetrain alternatives: Anaplan, Planful, Vena
Grok 4.1 FastCube, Datarails alternatives: Drivetrain, Limelight, Pigment, Vena
Mistral SmallDatarails, Limelight alternatives: Cube, Planful, Vena
Llama 4 MaverickDatarails alternatives: Abacum, Cube, Lucanet xP&A, Mosaic, Vena
Kimi K2Datarails alternatives: Aleph, Centage Planning Maestro, Cube
GLM 4.7 FlashXDatarails alternatives: Cube, Drivetrain, Mosaic, Planful
MiniMax M2.5Datarails alternatives: Cube, Planful

Neither was the first choice, one was named

2 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashMosaic, Pigment alternatives: Centage Planning Maestro, Cube, Datarails, Planful, Vena
DeepSeek V4 FlashLimelight alternatives: Abacum, Cube, Datarails, Pigment, Planful

Neither was named

2 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Qwen 3.7 FlashCube alternatives: Fathom, Float, Jedox, Jirav, Planful, Vena

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Microsoft Excel leads by four points.
Microsoft Excel6%#9 of 13
Datarails2%#10 of 13
The full small business standing →
Mid-marketThe figures above
The order flips: Datarails leads at mid-market.
Datarails19%#1 of 8
Microsoft Excel11%#4 of 8
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Datarails0%#– of 7
Microsoft Excel0%#– of 7
The full enterprise standing →

What the models said about Datarails

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“Avoid pricier dedicated tools like Finmark ($50+/month) or Datarails until revenue grows” Grok 4.1 Fast · budget prompt · hard negative
“Datarails is widely considered the best financial modeling software for most mid-market B2B companies” MiniMax M2.5 · direct prompt · first choice
“If you rely heavily on Excel and want a seamless transition, Datarails is the top pick.” Mistral Small · direct prompt · first choice

What the models said about Microsoft Excel

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Microsoft Excel | General‑purpose financial modeling | Dominant in finance, powerful formulas, Python in Excel, AI Copilot, wide ecosystem” GLM 4.7 FlashX · comparative prompt · first choice
“Microsoft Excel or Google Sheets remain the practical sweet spot, offering functionality, familiarity, and affordability.” Claude Haiku 4.5 · budget prompt · first choice
“For many small businesses, the absolute best tool is the one you likely already own.” Qwen 3.7 Flash · budget prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.