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Compensation management · October 2026 Edition

Comprehensive vs CompUp

Two of fourteen models named Comprehensive first on the direct prompt; two named CompUp. Comprehensive was named by eight of the fourteen models and CompUp by eight and Comprehensive carries 16 labels and CompUp 14, so the shares are not directly comparable.

Comprehensive

accepted challenger

Named in two categories this edition.

CompUp

accepted challenger

Named in three categories this edition.

First-choice share9%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 13; printed, not drawn.
Labels1614A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Comprehensive reading right to left. Rank and label count are printed, not drawn.Pave vs Comprehensive · Pave vs CompUp · Ravio vs Comprehensive

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 compensation 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.
ComprehensiveFirst choices, of fourteen modelsCompUp
Direct22
Paraphrase21
Comparative00
Budget-constrained02
Scale-constrained10
Negative00
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 Comprehensive and CompUp 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
Comprehensive CompUp first choice named as an alternative argued againstblank: not namedEach cell is one answer, Comprehensive on the left and CompUp on the right.

The direct prompt

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

Comprehensive first, CompUp not the choice

2 of 14 modelsCompUp was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashComprehensive, Pave alternatives: CaptivateIQ, Lattice Compensation, Payscale Ascent
Kimi K2Comprehensive alternatives: CaptivateIQ, Lattice Compensate, Pave, Ravio

CompUp first, Comprehensive not the choice

2 of 14 modelsComprehensive was named in the answer but not as the choice, or not at all.
Llama 4 MaverickCompUp, Paylocity
MiniMax M2.5CompUp alternatives: CaptivateIQ, Figures, Paylocity, Pequity

Neither was the first choice, one was named

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Perplexity SonarCompport alternatives: CaptivateIQ, CompUp, HiBob, Payscale Ascent, Ravio
Mistral SmallRavio alternatives: CompUp, Pave, Payscale, beqom
GLM 4.7 FlashXPayscale Ascent alternatives: BambooHR Compensation, CompUp, Comprehensive, Figures, Lattice Compensate, Pave, Paycor, Ravio

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5HiBob alternatives: Qobra, Salary.com, Visdum, beqom
GPT-5.4 miniCaptivateIQ alternatives: Everstage, QuotaPath, Spiff
Gemini 3.5 FlashCaptivateIQ, Pave alternatives: Barley, Everstage, HiBob, QuotaPath, Salesforce Spiff
Grok 4.1 FastPaycom alternatives: Comprehensive.io, HiBob, QuotaPath, Salary.com, Visdum
Qwen 3.7 FlashQuotaPath alternatives: Paylocity, Performio, Ravio, Visdum
GPT-6 LunaCaptivateIQ alternatives: Lattice Compensation, Payscale, Performio, Salesforce Spiff
Muse Glimmer 30Bno 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
Level: the same share of first choices.
Comprehensive4%#6 of 16
CompUp4%#– of 16
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Comprehensive9%#3 of 13
CompUp9%#4 of 13
The full mid-market standing →
Enterprise
CompUp leads by two points.
CompUp2%#– of 15
Comprehensive0%#– of 15
The full enterprise standing →

What the models said about Comprehensive

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

“Prioritize platforms like Comprehensive, Figures.hr, Salary.com CompAnalyst, Paycom, or Ravio, which are frequently recommended for this size” Grok 4.1 Fast · scale prompt · first choice
“Start with Comprehensive if you want an all-in-one platform for salary planning, equity management, and compensation reviews” Kimi K2 · paraphrase prompt · first choice
“I'd recommend evaluating Compport and Comprehensive first since both are specifically positioned for mid-market companies.” Claude Haiku 4.5 · paraphrase prompt · first choice

What the models said about CompUp

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

“CompUp appears particularly well-suited for mid-market and enterprise organizations running complex, multi-country compensation cycles.” MiniMax M2.5 · 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.