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Corporate performance management · October 2026 Edition

Prophix vs Pigment

Four of fourteen models named Prophix first on the direct prompt; zero named Pigment. Prophix was named by thirteen of the fourteen models and Pigment by seven and Prophix carries 39 labels and Pigment 11, so the shares are not directly comparable.

Prophix

accepted challenger

Named in nine categories this edition.

Pigment

accepted challenger

Named in six categories this edition.

First-choice share17%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate3%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#8A position in a field of 14; printed, not drawn.
Labels3911A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Prophix reading right to left. Rank and label count are printed, not drawn.Planful was named alongside these two in thirteen of the fourteen direct answers. Planful vs Prophix · Planful vs Pigment · Prophix vs Vena

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 corporate performance 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.
ProphixFirst choices, of fourteen modelsPigment
Direct40
Paraphrase21
Comparative001 against Prophix
Budget-constrained30
Scale-constrained10
Negative01
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 Prophix and Pigment 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
Prophix Pigment first choice named as an alternative argued againstblank: not namedEach cell is one answer, Prophix on the left and Pigment on the right.

The direct prompt

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

Prophix first, Pigment not the choice

4 of 14 modelsPigment was named in the answer but not as the choice, or not at all.
Grok 4.1 FastPlanful, Prophix alternatives: OneStream, Workday Adaptive Planning
Mistral SmallProfitbase EPM, Prophix alternatives: IBM Planning Analytics, Oracle Fusion Cloud EPM, Phocas Software
GLM 4.7 FlashXCube, Prophix alternatives: Planful
Muse Glimmer 30BPlanful, Prophix alternatives: Cube, Workday Adaptive Planning

Neither was the first choice, one was named

8 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Drivetrain alternatives: Jedox, Planful, Prophix, Vena, Workday Adaptive Planning
Gemini 3.5 FlashCube, Vena alternatives: Abacum, Datarails, Mosaic, Pigment, Planful, Prophix
Perplexity SonarPlanful alternatives: Datarails, Drivetrain, Prophix, Workday Adaptive Planning
DeepSeek V4 FlashPlanful alternatives: Drivetrain, Pigment, Prophix, Vena
Llama 4 MaverickPlanful alternatives: Prophix, Workday Adaptive Planning
Qwen 3.7 FlashPlanful alternatives: Drivetrain, Prophix
Kimi K2Datarails, Drivetrain, Vena alternatives: Cube, Planful, Prophix
MiniMax M2.5Planful, Workday Adaptive Planning alternatives: Cube, Prophix, Vena

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniPlanful, Vena alternatives: Board, Jedox, OneStream, Oracle Fusion Cloud EPM
GPT-6 LunaPlanful alternatives: NetSuite Planning and Budgeting, Vena, Workday Adaptive Planning

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
Level: the same share of first choices.
Prophix2%#7 of 13
Pigment2%#– of 13
The full small business standing →
Mid-marketThe figures above
Prophix leads by fifteen points.
Prophix17%#2 of 14
Pigment2%#8 of 14
The full mid-market standing →
Enterprise
The order flips: Pigment leads at enterprise.
Pigment2%#– of 12
Prophix0%#11 of 12
The full enterprise standing →

What the models said about Prophix

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

“easy to roll out and maintain but "doesn't allow for deep customization."” Muse Glimmer 30B · comparative prompt · soft negative
“Prophix is the strongest overall EPM option in these results because it is specifically described as a low-cost entry” Perplexity Sonar · budget prompt · first choice

What the models said about Pigment

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

“Pigment (Best for Collaborative, Cross-Functional Planning)... has rapidly become a favorite for modern B2B SaaS and services companies” Gemini 3.5 Flash · paraphrase prompt · first choice
“Safer bets if cautious: Newer/lower-implementation options like Pigment, Planful, Prophix, or Drivetrain” Grok 4.1 Fast · negative prompt · first choice
Also compared
Planful vs ProphixPlanful vs PigmentProphix vs VenaProphix vs Workday Adaptive PlanningProphix vs CubeProphix vs DatarailsProphix vs JedoxVena vs PigmentWorkday Adaptive Planning vs PigmentCube vs PigmentDatarails vs PigmentJedox vs PigmentAll twenty-eight head-to-head pages and the full corporate performance ma 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.