Gane Index
All indexesEvery index and its categoriesGTMMarketing, sales, customer and revenue operations softwareITSecurity, IT operations, cloud, developer and data softwareHRHR, payroll, recruiting, performance and learning softwareFinanceAccounting, planning, spend, billing and treasury software
Claim your listing
Index › Finance › Accounting and close › Financial close manageme › FloQast vs Datarails
Financial close management · November 2026 Edition

FloQast vs Datarails

Twelve of fourteen models named FloQast first on the direct prompt; zero named Datarails. FloQast was named by fourteen of the fourteen models and Datarails by nine and FloQast carries 69 labels and Datarails 12, so the shares are not directly comparable.

FloQast

endorsed leader

Named in seven categories this edition.

Datarails

accepted challenger

Named in ten categories this edition.

First-choice share53%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate12%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#6A position in a field of 14; printed, not drawn.
Labels6912A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, FloQast reading right to left. Rank and label count are printed, not drawn.Prophix was named alongside these two in eight of the fourteen direct answers. FloQast vs Numeric · FloQast vs Prophix · FloQast vs DOKKA Close

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 close management page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
FloQastFirst choices, of fourteen modelsDatarails
Direct120
Paraphrase140
Comparative70
Budget-constrained216 against FloQast
Scale-constrained30
Negative302 against FloQast
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where FloQast and Datarails stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
FloQast Datarails first choice named as an alternative argued againstblank: not namedEach cell is one answer, FloQast on the left and Datarails on the right.

The direct prompt

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

FloQast first, Datarails an alternative

12 of 14 modelsDatarails was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5FloQast alternatives: DOKKA Close, Trintech Adra
GPT-5.4 miniFloQast alternatives: BlackLine, Vena
Gemini 3.5 FlashFloQast alternatives: BlackLine, Numeric, Planful, Trintech Adra, Vena
Perplexity SonarFloQast alternatives: DOKKA Close, Numeric, Prophix, Trintech Adra
Grok 4.20FloQast alternatives: BlackLine, Prophix, Workiva
Mistral SmallFloQast, Prophix alternatives: BlackLine, DOKKA Close
DeepSeek V4 FlashFloQast alternatives: BlackLine, Datarails, Prophix, Sage Intacct
Qwen 3.7 FlashFloQast alternatives: Numeric, PivotXL, Prophix
Kimi K2FloQast alternatives: Prophix, Trintech Adra
MiniMax M2.5FloQast alternatives: Adra Suite, BlackLine, Sage Intacct, Trintech
GPT-6 LunaFloQast alternatives: BlackLine, Numeric, Trintech Adra
Muse Glimmer 30BFloQast alternatives: BlackLine, Prophix, Trintech

Neither was the first choice, one was named

1 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GLM 4.7 FlashXProphix alternatives: Cube, FloQast, Numeric

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 Maverickno first choice

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
FloQast leads by nineteen points.
FloQast28%#1 of 12
Datarails9%#4 of 12
The full small business standing →
Mid-marketThe figures above
FloQast leads by fifty-one points.
FloQast53%#1 of 14
Datarails2%#6 of 14
The full mid-market standing →
Enterprise
FloQast leads by eight points.
FloQast8%#2 of 12
Datarails0%#– of 12
The full enterprise standing →

What the models said about FloQast

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

“Mid-Market Tools (Avoid for Large Enterprises) Tools like FloQast ($30k-$80k/year) are designed for mid-market companies and often lack the scalability” Muse Glimmer 30B · negative prompt · hard negative
“Avoid FloQast and premium options like BlackLine or CCH Tagetik” DeepSeek V4 Flash · budget prompt · hard negative
“avoid enterprise-focused tools like BlackLine, FloQast, or Workiva” Grok 4.20 · budget prompt · hard negative
“Currently the market leader. Extremely high usability, great ecosystem, highly scalable. (Often the default choice for companies growing past 200 employees).” Qwen 3.7 Flash · scale prompt · first choice

What the models said about Datarails

No label in this category carried a quote.

Also compared
FloQast vs NumericFloQast vs ProphixFloQast vs DOKKA CloseFloQast vs PlanfulFloQast vs BlackLineNumeric vs DatarailsProphix vs DatarailsDOKKA Close vs DatarailsPlanful vs DatarailsDatarails vs BlackLineAll twenty-one head-to-head pages and the full financial close manageme standing

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.