HR AI Index
Index › Compensation and total rewards › Compensation benchmarkin › Enterprise › September 2026 Edition

Compensation benchmarking data for enterprise buyers

Asked as “salary benchmarking data provider”, and as “compensation survey data”, on behalf of an enterprise B2B company. 61 first choices recorded across the direct, paraphrase, budget and scale prompts, twelve models each.
Standing
Mercer
Contested
26% of first choices, contested.
ShowinginAll 50 categories →

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small businessPave32%ContestedStanding →Mid-marketPayscale24%ContestedStanding →EnterpriseMercer26%ContestedThis page

01The standing

Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all twelve models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
01Mercer26%14%35accepted challenger
02Radford16%12%24accepted challenger
03Willis Towers Watson11%14%22accepted challenger
04Pave8%21%19accepted challenger
05Korn Ferry3%7%15accepted challenger
06Salary.com3%14%14accepted challenger
07Payscale3%24%21accepted challenger
08Ravio2%20%15accepted challenger
Show the two products at 0%, ordered by negative rate
10Gartner0%21%14accepted challenger
09Deloitte0%8%12accepted challenger
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its vendor page.
Head to head
Payscale vs PavePayscale vs Comprehensive.ioPave vs Comprehensive.io

Recommended versus criticized

Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.

Criticized challengerCriticized default
Negative label rate →
01
02
03
04
05
06
07
08
09
10
Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Mercer26%
02Radford16%
03Willis Towers Watson11%
04Pave8%
05Korn Ferry3%
06Salary.com3%
07Payscale3%
08Ravio2%
09Deloitte0%
10Gartner0%

02What they warned about

Zero of twelve models held their first choice under the paraphrase. 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 and MiniMax M2.5 changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Mercer
14%
5 of 35 labels negative · 5 of 12 models · 2 hard negative
“Why you should avoid traditional providers (Mercer, Radford, Willis Towers Watson)” GLM 4.7 FlashX, budget prompt
Payscale
24%
5 of 21 labels negative · 4 of 12 models · 2 hard negative
“Payscale (for high-complexity executive roles). Why to avoid: These platforms often suffer from "self-selection bias."” Qwen 3.7 Flash, negative prompt
Radford
12%
3 of 24 labels negative · 3 of 12 models · 2 hard negative
“Providers to Avoid for "Predictable Total Cost" ... Custom pricing $15K–$80K+; participation requirements” Kimi K2, budget prompt
Willis Towers Watson
14%
3 of 22 labels negative · 3 of 12 models · 2 hard negative
“Why you should avoid traditional providers (Mercer, Radford, Willis Towers Watson)” GLM 4.7 FlashX, budget prompt

03What they cite

Citations exist only for the models that return a source list: twelve of the twelve in this edition, and all six flagship models on the expanded tier.

Sites the answers cite

61 of 72 answers in this category came back with a source list, from 12 of 12 models: citations where the model returns them, or the search results it consulted. 5 of those lists are Google grounding redirects that name no site and are left out of the counts. 888 links across 279 sites, every framing counted. Ranked by the number of answers carrying the site or page.

ravio.com
vendor site · Ravio39 answers · 116 citations · 11 models
worldmetrics.org
29 answers · 60 citations · 10 models
zipdo.co
26 answers · 34 citations · 9 models
salarycube.com
vendor site · SalaryCube22 answers · 39 citations · 10 models
gitnux.org
19 answers · 31 citations · 9 models
comprehensive.io
vendor site · Comprehensive16 answers · 18 citations · 9 models
captivateiq.com
vendor site · CaptivateIQ13 answers · 14 citations · 7 models
ficstar.com
vendor site · Ficstar13 answers · 13 citations · 8 models
payscale.com
vendor site · Payscale12 answers · 13 citations · 7 models
imercer.com
11 answers · 16 citations · 7 models
salary.com
vendor site · Salary.com11 answers · 15 citations · 7 models
bestrecruitingtools.com
10 answers · 10 citations · 7 models

Pages the answers cite

The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.

ravio.com/blog/compensation-benchmarking-companies
30 answers · 10 models
ravio.com/blog/the-best-tools-for-salary-benchmarking
21 answers · 9 models
comprehensive.io/content/best-compensation-benchmarking-data-sources
15 answers · 8 models
ravio.com/blog/salary-survey-providers
15 answers · 9 models
worldmetrics.org/service/it-benchmarking
15 answers · 9 models
captivateiq.com/blog/compensation-benchmarking-software
13 answers · 7 models
ficstar.com/best-compensation-benchmarking-data-providers-2026
13 answers · 8 models
payscale.com/
11 answers · 6 models
worldmetrics.org/service/corporate-benchmarking
11 answers · 7 models
bestrecruitingtools.com/blog/best-compensation-management-software-enterpri…
10 answers · 7 models

04How they answered

Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ModelDirect“What is the best salary benchmarking data provider for an enterprise B2B company?”Paraphrase“Which compensation survey data would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade benchmarking providers and how do they differ?”Budget-constrained“What is the best salary benchmarking data provider for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a salary benchmarking data provider. What should we look at?”Negative“Which benchmarking providers should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Mercer, Radford
Seven alternativesCulpepper, Korn Ferry, Pave, Payscale, Ravio, Salary.com, Willis Towers Watson
Mercer, Radford, Willis Towers WatsonChanged
One alternativePave
no first choicePayscale
Two alternativesSalary.com, Willis Towers Watson
against: Mercerno first choicenothing named
GPT-5.4 miniAon's Radford McLagan Compensation Database
Three alternativesMercer, Payscale, Salary.com
Mercer, WTWChanged
Three alternativesAon Radford, Korn Ferry, SHRM benefits data
Gartner
Two alternativesForrester, Gartner Peer Insights
Mercer’s TRS / TAAP+
One alternativeAon Radford
no first choicenothing named
Gemini 3.5 FlashPave, Radford
Three alternativesMercer, Payscale MarketPay, WTW
Aon's Radford McLagan Compensation Database, Mercer Benchmark Database, Willis Towers WatsonChanged
Three alternativesPayscale, Salary.com CompAnalyst, The Alexander Group
no first choicePave
Two alternativesCompa, Salary.com
against: Aon Radford, WTWno first choice
Two alternativesMercer, Radford/Aon
against: Eqtble, Figures, Paveagainst: Korn Ferry, Mercer, Radford
Perplexity SonarMercer
Two alternativesPave, Ravio
Mercer, WTW (Willis Towers Watson) Rewards Data IntelligenceChanged
Two alternativesKorn Ferry Pay, Radford
Deloitte
Eight alternativesBCG, Bain & Company, Gartner, Guidehouse, KPMG, Kearney, PwC, The Hackett Group
against: Computer EconomicsMercer
Two alternativesComprehensive.io, Ravio
no first choicenothing named
Grok 4.1 FastRadford
Four alternativesKorn Ferry, Mercer, Salary.com, Willis Towers Watson
against: Glassdoor, Pave, RavioMercerChanged
Four alternativesKorn Ferry, Radford, Willis Towers Watson, WorldatWork Salary Budget Survey & Data Center
against: Payscale, Salary.comDeloitte
Twelve alternativesAPQC, BCG, Bain & Company, Computer Economics, EY, Forrester, Gartner, IDC, ISG, KPMG, McKinsey, PwC
Radford
Two alternativesMercer, Willis Towers Watson
against: Lattice, Pave, Payscale, Ravio, Salary.comPayscale, Salary.com
Two alternativesMercer, Radford/Aon
against: Bain, Delve, Forrester, Gartner, Hackett Group, Meta's Llama AI benchmarks, Oracle, PwC
Mistral SmallMercer
Two alternativesAon, Deloitte
Aon (formerly Radford) Global Compensation Survey, Mercer Total Remuneration Survey, Willis Towers Watson (WTW) Global Compensation SurveyChanged
Three alternativesCulpepper, ECA International, Radford (now Aon) Sales Compensation Survey
against: PayscaleDeloitte
Six alternativesAccenture, Bain & Company, Boston Consulting Group, EY, KPMG, PwC
against: McKinsey & CompanyKorn Ferry, Mercer, Radford, Willis Towers Watson
Two alternativesPayscale, SalaryCube
no first choiceagainst: BAPCo, Chatbot Arena
DeepSeek V4 FlashRadford
Five alternativesCarta Total Comp, Korn Ferry, Mercer, Pave, Willis Towers Watson
Mercer Total Remuneration Survey (TRS) / Mercer WIN, RadfordChanged
Three alternativesCulpepper, Korn Ferry, Willis Towers Watson
against: BLS OEWS, Payscale / Salary.comSalary.com CompAnalyst
One alternativeRevelio Labs
Mercer
Three alternativesKorn Ferry, Radford, Willis Towers Watson
against: Lattice Compensate, OpenComp, Pave, Payscale MarketPay, Raviono first choiceagainst: Forrester, Gartner, Oracle
Llama 4 MaverickMercer
Four alternativesFicstar, PayScale Insight, Radford, Salary.com CompAnalyst
Korn Ferry Pay, Mercer, RavioChangedDeloitte Consulting
Three alternativesBoston Consulting Group, KPMG Advisory, PwC Advisory
no first choiceno first choicenothing named
Qwen 3.7 FlashRadford
Three alternativesKorn Ferry, Mercer, Willis Towers Watson
Mercer, Willis Towers WatsonChanged
Two alternativesAon, Payscale
no first choiceOptionHR, Salary.com
Four alternativesAon, Mercer, Payscale, Willis Towers Watson
against: Glassdoor, Indeedno first choiceagainst: Aon, Glassdoor, Hays, Indeed, Mercer, Michael Page, Payscale, Robert Half, Willis Towers Watson
Kimi K2Radford
Two alternativesMercer, WTW
Mercer, Willis Towers WatsonChanged
Two alternativesKorn Ferry, Radford
Gartner
Four alternativesAPQC, Computer Economics, KPMG, The Hackett Group
Pave, Salary.com CompAnalyst
Two alternativesCompa, Figures
against: Levels.fyi, Mercer, Payscale, Radford, Willis Towers Watsonno first choiceagainst: Benchmark / benchmark.co.com, Benchmark Consulting Group LLC, Forrester, Gartner, IDC, MarketResearch.com, MarketsandMarkets, ResearchandMarkets.com, Transparency Market Research
GLM 4.7 FlashXMercer – Global Total Remuneration Survey
Five alternativesPave, Radford, Ravio, Salary.com CompAnalyst, Willis Towers Watson
Mercer, Willis Towers WatsonChanged
One alternativeFicstar
no first choicePave
One alternativeOpenComp
against: Mercer, Radford, Willis Towers Watsonno first choiceagainst: BCG, Bain, Deloitte, EY, KPMG, PwC
MiniMax M2.5Korn Ferry, Mercer, Willis Towers Watson
Three alternativesPayscale, Radford, Ravio
Mercer Global Compensation Database, Willis Towers Watson (WTW) "General Industry Compensation Survey"Changed
Three alternativesKorn Ferry Global Executive Compensation Survey, Option Impact Equity Benchmarking, Radford Global Technology Survey
Deloitte Consulting
Six alternativesBain & Company, Boston Consulting Group, EY Advisory, KPMG Advisory, McKinsey & Company, PwC Advisory
Pave
Two alternativesMercer, Radford
no first choiceagainst: Agri Stats, Optimal Blue, STR
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against

05The record

One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Seventy-two rows: every prompt, every model, every answer.
PromptModelVersion stringTime (UTC)SearchedSourcesLatency
Direct recommendationClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 18:27yes97 s
Direct recommendationGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 18:12yes45 s
Direct recommendationGemini 3.5 Flashgemini-3.5-flash2026-09-17 20:05yes1526 s
Direct recommendationPerplexity Sonarsonar2026-09-17 18:56yes206 s
Direct recommendationGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 19:42yes2918 s
Direct recommendationMistral Smallmistral/mistral-small via mistral2026-09-17 21:06yes96 s
Direct recommendationDeepSeek V4 Flashdeepseek/deepseek-v4-flash via fireworks2026-09-17 19:24yes1720 s
Direct recommendationLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 20:55yes53 s
Direct recommendationQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 19:53no028 s
Direct recommendationKimi K2moonshotai/kimi-k2 via novita2026-09-17 21:36yes1539 s
Direct recommendationGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 21:04yes2436 s
Direct recommendationMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 20:18yes940 s
ParaphraseClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 19:34yes1310 s
ParaphraseGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 18:54yes47 s
ParaphraseGemini 3.5 Flashgemini-3.5-flash2026-09-17 18:22yes1125 s
ParaphrasePerplexity Sonarsonar2026-09-17 19:50yes208 s
ParaphraseGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 18:26yes1712 s
ParaphraseMistral Smallmistral/mistral-small via mistral2026-09-17 21:13no07 s
ParaphraseDeepSeek V4 Flashdeepseek/deepseek-v4-flash via fireworks2026-09-17 21:15yes1224 s
ParaphraseLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 18:43yes53 s
ParaphraseQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 19:37yes525 s
ParaphraseKimi K2moonshotai/kimi-k2 via novita2026-09-17 19:08yes1124 s
ParaphraseGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 19:00yes1021 s
ParaphraseMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 21:24no066 s
ComparativeClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 19:01yes97 s
ComparativeGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 21:19yes58 s
ComparativeGemini 3.5 Flashgemini-3.5-flash2026-09-17 19:34yes2524 s
ComparativePerplexity Sonarsonar2026-09-17 20:14yes209 s
ComparativeGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 21:22yes3321 s
ComparativeMistral Smallmistral/mistral-small via mistral2026-09-17 21:30yes56 s
ComparativeDeepSeek V4 Flashdeepseek/deepseek-v4-flash via fireworks2026-09-17 18:40yes3054 s
ComparativeLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 19:30yes52 s
ComparativeQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 18:58no029 s
ComparativeKimi K2moonshotai/kimi-k2 via novita2026-09-17 18:45yes1527 s
ComparativeGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 21:25yes1748 s
ComparativeMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 18:09yes729 s
Budget constrainedClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 20:19yes169 s
Budget constrainedGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 18:10yes35 s
Budget constrainedGemini 3.5 Flashgemini-3.5-flash2026-09-17 18:05yes1565 s
Budget constrainedPerplexity Sonarsonar2026-09-17 18:39yes208 s
Budget constrainedGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 21:16yes3024 s
Budget constrainedMistral Smallmistral/mistral-small via mistral2026-09-17 21:40yes1110 s
Budget constrainedDeepSeek V4 Flashdeepseek/deepseek-v4-flash via fireworks2026-09-17 18:55yes2725 s
Budget constrainedLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 18:00yes53 s
Budget constrainedQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 19:18no034 s
Budget constrainedKimi K2moonshotai/kimi-k2 via novita2026-09-17 19:57yes2839 s
Budget constrainedGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 19:53yes31266 s
Budget constrainedMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 19:11yes1960 s
Scale constrainedClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 20:57yes1814 s
Scale constrainedGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 19:08no012 s
Scale constrainedGemini 3.5 Flashgemini-3.5-flash2026-09-17 18:20no017 s
Scale constrainedPerplexity Sonarsonar2026-09-17 19:36yes2011 s
Scale constrainedGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 19:49yes2014 s
Scale constrainedMistral Smallmistral/mistral-small via mistral2026-09-17 20:48no08 s
Scale constrainedDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-09-17 18:14yes2762 s
Scale constrainedLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 20:27yes53 s
Scale constrainedQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 20:39yes531 s
Scale constrainedKimi K2moonshotai/kimi-k2 via novita2026-09-17 21:13yes2538 s
Scale constrainedGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 19:44yes1551 s
Scale constrainedMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 19:48no011 s
Negative framingClaude Haiku 4.5claude-haiku-4-5-202510012026-09-17 20:13yes1811 s
Negative framingGPT-5.4 minigpt-5.4-mini-2026-03-172026-09-17 18:12no06 s
Negative framingGemini 3.5 Flashgemini-3.5-flash2026-09-17 22:00yes2857 s
Negative framingPerplexity Sonarsonar2026-09-17 19:59yes206 s
Negative framingGrok 4.1 Fastspacexai/grok-4.1-fast-non-reasoning via vertex2026-09-17 19:13yes1914 s
Negative framingMistral Smallmistral/mistral-small via mistral2026-09-17 20:00yes1511 s
Negative framingDeepSeek V4 Flashdeepseek/deepseek-v4-flash via fireworks2026-09-17 21:21yes2934 s
Negative framingLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-09-17 19:45yes53 s
Negative framingQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-09-17 20:17no033 s
Negative framingKimi K2moonshotai/kimi-k2 via novita2026-09-17 18:13yes2443 s
Negative framingGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-09-17 20:09yes27135 s
Negative framingMiniMax M2.5minimax/minimax-m2.5 via minimax2026-09-17 20:08yes2280 s

Normalization in this category

Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.

Category-scoped readings
None. Every name in this category resolved on its own.
Unresolved, counted raw
A.T. Kearney
ALM Intelligence
APEC (Association of Professional Executives of Canada) Compensation Survey
Agri Stats
Aon (formerly Radford) Global Compensation Survey
BAPCo
Benchmark Consulting Group LLC
Chatbot Arena
Compensa
Compup.io
Crayon
Custom Survey Professionals
Digimind
ECA International
Empsight
Eqtble
GK
Gartner Peer Insights
Hackett Group
Hired\u2019s Salary Calculator
IBM Consulting
Kennedy Consulting Research
Klue
Kompyte
Korn Ferry Global Executive Compensation Survey
MarketsandMarkets
Mercer Global Compensation Database
Mercer Total Remuneration Survey (TRS)
Mercer Total Remuneration Survey (TRS) / Mercer WIN
Mercer – Global Total Remuneration Survey (TRS)
Mercer’s TRS / TAAP+
Meta's Llama AI benchmarks
Omdia
Optimal Blue
Option Impact Equity Benchmarking
OptionHR
Radford (now Aon) Sales Compensation Survey
Radford Global Technology Survey
Revelio Labs
SHRM benefits data
SPEC
STR (Smith Travel Research)
TPC
TSIA
The Alexander Group
WTW (Willis Towers Watson) Rewards Data Intelligence
Willis Towers Watson (WTW) "General Industry Compensation Survey"
Willis Towers Watson (WTW) Global Compensation Survey
World Metrics
WorldatWork Salary Budget Survey & Data Center
Discontinued, still offered
No shut-down product was recommended here.

Also in compensation and total rewards

The other categories of this function, with the leader in each.
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