Index › HR › Compensation and total rewards › Compensation benchmarkin › Pave vs Comprehensive.io
Compensation benchmarking data · November 2026 Edition

Pave vs Comprehensive.io

Three of fourteen models named Pave first on the direct prompt; one named Comprehensive.io. Pave was named by fourteen of the fourteen models and Comprehensive.io by eleven and Pave carries 36 labels and Comprehensive.io 15, so the shares are not directly comparable.

Pave

accepted challenger

Named in five categories this edition.

Comprehensive.io

accepted challenger

Named in three categories this edition.

First-choice share15%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#2#3A position in a field of 9; printed, not drawn.
Labels3615A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Pave reading right to left. Rank and label count are printed, not drawn.Payscale was named alongside these two in eleven of the fourteen direct answers. Payscale vs Pave · Payscale vs Comprehensive.io · Pave vs Salary.com CompAnalyst

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 benchmarking data page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
PaveFirst choices, of fourteen modelsComprehensive.io
Direct31
Paraphrase00
Comparative10
Budget-constrained44
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.

Across every category in the November 2026 Edition, Pave and Comprehensive.io were named in the same answer thirty-nine times, of the 220 answers naming Pave and the 62 naming Comprehensive.io. In those answers Comprehensive.io took the first choice four times and Pave nineteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Pave and Comprehensive.io 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
Pave Comprehensive.io first choice named as an alternative argued againstblank: not namedEach cell is one answer, Pave on the left and Comprehensive.io on the right.

The direct prompt

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

Pave first, Comprehensive.io not the choice

3 of 14 modelsComprehensive.io was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Pave, SalaryCube alternatives: CompUp, OpenComp, Payscale Ascent
Gemini 3.5 FlashPave alternatives: Carta Total Compensation, Payscale, Salary.com CompAnalyst
Mistral SmallPave alternatives: Mercer Total Remuneration Survey, Payscale

Comprehensive.io first, Pave an alternative

1 of 14 modelsPave was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashComprehensive.io alternatives: Figures, Pave, Payscale, Salary.com CompAnalyst

Neither was the first choice, one was named

10 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniSalary.com CompAnalyst alternatives: Compensation-IQ, Pave, Payscale Ascent
Perplexity SonarPayscale alternatives: Pave, Ravio, SalaryCube
Grok 4.20Payscale alternatives: Pave, Ravio, Salary.com CompAnalyst
DeepSeek V4 FlashPayscale alternatives: Mercer Benchmark Database, Pave, Ravio, SalaryCube
Llama 4 MaverickSalaryCube alternatives: Mercer Total Remuneration Survey, Pave, Payscale
Kimi K2Payscale alternatives: Mercer Total Remuneration Survey, Pave, Radford, Salary.com CompAnalyst
GLM 4.7 FlashXFigures, SalaryCube Comp Planning alternatives: Pave, Salary.com CompAnalyst
MiniMax M2.5CompAnalyst, Payscale alternatives: Pave
GPT-6 LunaPayscale alternatives: Pave
Muse Glimmer 30BPayscale alternatives: CompAnalyst, Comprehensive.io, Pave, Salary.com CompAnalyst, SalaryCube

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
Pave leads by twelve points.
Pave19%#1 of 10
Comprehensive.io7%#4 of 10
The full small business standing →
Mid-marketThe figures above
Pave leads by five points.
Pave15%#2 of 9
Comprehensive.io9%#3 of 9
The full mid-market standing →
Enterprise
Pave leads by three points.
Pave3%#7 of 9
Comprehensive.io0%#– of 9
The full enterprise standing →

What the models said about Pave

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

“Pave's free Market Data Lite tier and Comprehensive's free salary data both give small teams real numbers at no cost” Claude Haiku 4.5 · budget prompt · first choice

What the models said about Comprehensive.io

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

“Pave's free Market Data Lite tier and Comprehensive's free salary data both give small teams real numbers at no cost” Claude Haiku 4.5 · budget prompt · first choice
“Comprehensive.io - offers free, daily-refreshed tech salary data with no survey submission requirement.” Llama 4 Maverick · budget prompt · first choice
“The Top All-Rounder: Comprehensive.io ... frequently cited as the best fit for the mid-market segment” Qwen 3.7 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.