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Financial modeling and scenario planning · September 2026 Edition

Cube vs Vena

Two of twelve models named Cube first on the direct prompt; zero named Vena. Cube was named by nine of the twelve models and Vena by twelve and Cube carries 18 labels and Vena 26, so the shares are not directly comparable.

Cube

accepted challenger

Named in nine categories this edition.

Vena

accepted challenger

Named in ten categories this edition.

First-choice share11%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.

Negative rate0%15%Negative labels as a share of the product's labels, 0 to 100.

Rank in category#3#5A position in a field of 8; printed, not drawn.

Labels1826A count; the two differ.

The two percentage rows are drawn on one 0 to 100 track, Cube reading right to left. Rank and label count are printed, not drawn.Datarails was named alongside these two in ten of the twelve direct answers. Datarails vs Cube · Datarails vs Vena · Google Sheets vs Cube

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.

CubeFirst choices, of twelve modelsVena

Direct201 against Vena

Paraphrase33

Comparative00

Budget-constrained003 against Vena

Scale-constrained00

Negative00

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.

Across every category in the September 2026 Edition, Cube and Vena were named in the same answer 139 times, of the 311 answers naming Cube and the 348 naming Vena. In those answers Vena took the first choice twelve times and Cube eighteen.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Cube and Vena stood in it.

Model	Direct	Paraphrase	Comparative	Budget-constrained	Scale-constrained	Negative
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

Cube

Vena

first choice

named as an alternative

argued againstblank: not namedEach cell is one answer, Cube on the left and Vena on the right.

The direct prompt

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

Cube first, Vena an alternative

2 of 12 modelsVena was named in the answer but not as the choice, or not at all.

Grok 4.1 FastCube, Datarails alternatives: Drivetrain, Limelight, Pigment, Vena

Qwen 3.7 FlashCube alternatives: Fathom, Float, Jedox, Jirav, Planful, Vena

Neither was the first choice, one was named

8 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

Perplexity SonarDatarails, Drivetrain alternatives: Anaplan, Planful, Vena

Mistral SmallDatarails, Limelight alternatives: Cube, Planful, Vena

DeepSeek V4 FlashLimelight alternatives: Abacum, Cube, Datarails, Pigment, Planful

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 named

2 of 12 modelsThe answer made no first choice from these two in this category.

Claude Haiku 4.5no first choice

GPT-5.4 miniDatarails alternatives: Abacum, Anaplan

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

Cube leads by six points.

Cube#4 of 13

Vena#– of 13

The full small business standing →

Mid-marketThe figures above

Cube leads by four points.

Cube#3 of 8

Vena#5 of 8

The full mid-market standing →

Enterprise

Cube leads by three points.

Cube#– of 7

Vena#6 of 7

The full enterprise standing →

What the models said about Cube

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

“Cube: This is currently one of the fastest-growing tools in this space.... | Loves Excel and hates change | Cube |” Qwen 3.7 Flash · direct prompt · first choice

“For a general mid-sized B2B company, Cube gives the best cost/value balance and adoption ease.” DeepSeek V4 Flash · paraphrase prompt · first choice

What the models said about Vena

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

“Vena or Planful are the top choices due to their balance of structure, Excel integration, and advanced scenario capabilities” Mistral Small · paraphrase prompt · first choice

Also compared

Datarails vs Cube Datarails vs Vena Google Sheets vs Cube Google Sheets vs Vena Cube vs Microsoft Excel Cube vs Planful Cube vs Workday Adaptive Planning Microsoft Excel vs Vena Vena vs Planful Vena vs Workday Adaptive Planning All twenty-one head-to-head pages and the full financial modeling 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.