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FP&A platforms · October 2026 Edition

Fathom vs Vena

Zero of fourteen models named Fathom first on the direct prompt; four named Vena. Fathom was named by eleven of the fourteen models and Vena by fourteen and Fathom carries 13 labels and Vena 60, so the shares are not directly comparable.

Fathom

accepted challenger

Named in eight categories this edition.

Vena

accepted challenger

Named in nine categories this edition.

First-choice share15%13%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%20%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 18; printed, not drawn.
Labels1360A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Fathom reading right to left. Rank and label count are printed, not drawn.Planful was named alongside these two in nine of the fourteen direct answers. Planful vs Fathom · Planful vs Vena · Fathom vs Cube

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 FP&A platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
FathomFirst choices, of fourteen modelsVena
Direct04
Paraphrase02
Comparative00
Budget-constrained803 against Vena
Scale-constrained01
Negative001 against Fathom · 9 against Vena
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 Fathom and Vena 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
GPT-6 Luna
Muse Glimmer 30B
Fathom Vena first choice named as an alternative argued againstblank: not namedEach cell is one answer, Fathom on the left and Vena on the right.

The direct prompt

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

Vena first, Fathom not the choice

4 of 14 modelsFathom was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashVena alternatives: Aleph, Bob Finance, Cube, Pigment, Planful
Grok 4.1 FastVena alternatives: Centage, Cube, Datarails, Planful
Qwen 3.7 FlashVena alternatives: Aleph, Cube, Planful
MiniMax M2.5Vena alternatives: Drivetrain, Parse

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniPlanful alternatives: Pigment, Vena
Perplexity SonarAbacum, Planful alternatives: Vena, Workday Adaptive Planning
Mistral SmallCentage alternatives: Abacum, Drivetrain, Planful, Prophix, Vena
Kimi K2Cube alternatives: Aleph, Datarails, Drivetrain, Jirav, Vena
GLM 4.7 FlashXAbacum, Drivetrain alternatives: Cube, Vena
GPT-6 LunaAbacum alternatives: Planful, Vena
Muse Glimmer 30BPigment alternatives: Abacum, Aleph, Centage, Cube, Datarails, Planful, Vena

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Aleph, Cube alternatives: Pigment, Prophix, Workday Adaptive Planning
DeepSeek V4 FlashDatarails, Drivetrain alternatives: Cube, Jirav, Planful, Prophix, Workday Adaptive Planning
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
Fathom leads by twenty-three points.
Fathom25%#1 of 16
Vena2%#10 of 16
The full small business standing →
Mid-marketThe figures above
Fathom leads by two points.
Fathom15%#2 of 18
Vena13%#3 of 18
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Fathom0%#– of 14
Vena0%#10 of 14
The full enterprise standing →

What the models said about Fathom

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

“users report missing features, upload/import problems, and limited customization” GPT-5.4 mini · negative prompt · soft negative
“For quick implementation: Cloud-based tools like Fathom or Finmark offer fast setup with reasonable pricing.” MiniMax M2.5 · budget prompt · first choice
“Top pick for budget-conscious SMBs ... Try Fathom's free trial—it's the sweet spot for cost vs. features.” Grok 4.1 Fast · budget prompt · first choice
“Start with Syft Analytics (free tier) or Fathom (~$44/month) if you need integrated forecasting.” Kimi K2 · budget 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. Four of four in this category shown.

“Strong negative quotes (e.g., "would rather eat a bullet than use it again"); 16-58% negative labels” Grok 4.1 Fast · negative prompt · hard negative
“Options to Avoid on a Limited Budget ... Vena — Median contract ~$34,000/year” DeepSeek V4 Flash · budget prompt · hard negative
“#1 in G2 Mid-Market Grid for Budgeting/Forecasting & Financial Analysis (Summer 2024)... For comprehensive planning: Vena or Planful (top G2 mid-market leaders).” Grok 4.1 Fast · direct prompt · first choice
“Best For: Mid-market companies ($50M–$500M+ revenue) that are deeply committed to Excel and need enterprise-grade security and workflows.” Gemini 3.5 Flash · direct 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.