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Compensation benchmarking data · November 2026 Edition

Payscale vs Pave

Seven of fourteen models named Payscale first on the direct prompt; three named Pave. Both were named by all fourteen models and Payscale carries 32 labels and Pave 36, so the shares are not directly comparable.

Payscale

accepted challenger

Named in four categories this edition.

Pave

accepted challenger

Named in five categories this edition.

First-choice share18%15%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate9%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#2A position in a field of 9; printed, not drawn.
Labels3236A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Payscale reading right to left. Rank and label count are printed, not drawn.Payscale vs Comprehensive.io · Payscale vs Salary.com CompAnalyst · Payscale vs Glassdoor

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.
PayscaleFirst choices, of fourteen modelsPave
Direct73
Paraphrase30
Comparative01
Budget-constrained042 against Payscale
Scale-constrained011 against Payscale
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, Payscale and Pave were named in the same answer eighty-eight times, of the 239 answers naming Payscale and the 220 naming Pave. In those answers Pave took the first choice twenty-five times and Payscale fourteen.

Every model, every framing

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

The direct prompt

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

Payscale first, Pave an alternative

7 of 14 modelsPave was named in the answer but not as the choice, or not at all.
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
Kimi K2Payscale alternatives: Mercer Total Remuneration Survey, Pave, Radford, 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

Pave first, Payscale an alternative

3 of 14 modelsPayscale 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

Neither was the first choice, one was named

4 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
Llama 4 MaverickSalaryCube alternatives: Mercer Total Remuneration Survey, Pave, Payscale
Qwen 3.7 FlashComprehensive.io alternatives: Figures, Pave, Payscale, Salary.com CompAnalyst
GLM 4.7 FlashXFigures, SalaryCube Comp Planning alternatives: Pave, Salary.com CompAnalyst

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 seven points.
Pave19%#1 of 10
Payscale12%#2 of 10
The full small business standing →
Mid-marketThe figures above
The order flips: Payscale leads at mid-market.
Payscale18%#1 of 9
Pave15%#2 of 9
The full mid-market standing →
Enterprise
Payscale leads by two points.
Payscale5%#5 of 9
Pave3%#7 of 9
The full enterprise standing →

What the models said about Payscale

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

“Data self-reported by employees (e.g., Glassdoor, Payscale). This is often inflated, noisy, and difficult to verify” Gemini 3.5 Flash · scale prompt · soft negative
“Best for: Growing companies ready to invest in compensation infrastructure” MiniMax M2.5 · budget prompt · soft negative
“full benchmarking requires subscriptions (avoid if budget is tight)” Grok 4.20 · budget prompt · soft negative
“Payscale for broad mid-market coverage ... Payscale Knowledge / Payscale. Real-time data with survey sourcing and broad job family coverage.” Muse Glimmer 30B · direct prompt · first choice
“Most mid-market companies find that Payscale strikes the best balance of cost, coverage, and functionality” Kimi K2 · direct prompt · first choice
“Payscale (or Payscale + CompAnalyst) – Strongest overall fit for most mid-sized B2B companies” Grok 4.20 · paraphrase prompt · first choice

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
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.