# Compensation benchmarking data for enterprise buyers: what AI models recommend, September 2026

HR AI Recommendation Index, September 2026 Edition. Asked as "salary benchmarking data provider" and as "compensation survey data", six framings each, to twelve models with search on, on behalf of an enterprise B2B company. Page: https://hr-ai-index.com/rewards/compensation-benchmarking-data/enterprise/

**Standing:** Mercer leads with 26% of first choices; verdict contested. 61 first choices across the direct, paraphrase, budget and scale prompts.

## First-choice share

| # | Product | Share | Negative rate | Labels |
|---|---|---|---|---|
| 1 | Mercer | 26% | 14% | 35 |
| 2 | Radford | 16% | 12% | 24 |
| 3 | Willis Towers Watson | 11% | 14% | 22 |
| 4 | Pave | 8% | 21% | 19 |
| 5 | Korn Ferry | 3% | 7% | 15 |
| 6 | Salary.com | 3% | 14% | 14 |
| 7 | Payscale | 3% | 24% | 21 |
| 8 | Ravio | 2% | 20% | 15 |
| 9 | Deloitte | 0% | 8% | 12 |
| 10 | Gartner | 0% | 21% | 14 |

## Each model's first choice on the direct prompt

- Claude Haiku 4.5: Mercer, Radford; alternatives Culpepper, Korn Ferry, Pave, Payscale
- GPT-5.4 mini: Aon's Radford McLagan Compensation Database; alternatives Mercer, Payscale, Salary.com
- Gemini 3.5 Flash: Pave, Radford; alternatives Mercer, Payscale MarketPay, WTW
- Perplexity Sonar: Mercer; alternatives Pave, Ravio
- Grok 4.1 Fast: Radford; alternatives Korn Ferry, Mercer, Salary.com, Willis Towers Watson
- Mistral Small: Mercer; alternatives Aon, Deloitte
- DeepSeek V4 Flash: Radford; alternatives Carta Total Comp, Korn Ferry, Mercer, Pave
- Llama 4 Maverick: Mercer; alternatives Ficstar, PayScale Insight, Radford, Salary.com CompAnalyst
- Qwen 3.7 Flash: Radford; alternatives Korn Ferry, Mercer, Willis Towers Watson
- Kimi K2: Radford; alternatives Mercer, WTW
- GLM 4.7 FlashX: Mercer – Global Total Remuneration Survey; alternatives Pave, Radford, Ravio, Salary.com CompAnalyst
- MiniMax M2.5: Korn Ferry, Mercer, Willis Towers Watson; alternatives Payscale, Radford, Ravio

## Sources the answers cite

61 of 72 answers came back with a source list, from 12 of 12 models. Sites named in the most answers:

- ravio.com: 39 answers, 116 citations
- worldmetrics.org: 29 answers, 60 citations
- zipdo.co: 26 answers, 34 citations
- salarycube.com: 22 answers, 39 citations
- gitnux.org: 19 answers, 31 citations
- comprehensive.io: 16 answers, 18 citations
- captivateiq.com: 13 answers, 14 citations
- ficstar.com: 13 answers, 13 citations

Pages named in the most answers:

- https://ravio.com/blog/compensation-benchmarking-companies (30 answers)
- https://ravio.com/blog/the-best-tools-for-salary-benchmarking (21 answers)
- https://comprehensive.io/content/best-compensation-benchmarking-data-sources (15 answers)
- https://ravio.com/blog/salary-survey-providers (15 answers)
- https://worldmetrics.org/service/it-benchmarking (15 answers)
- https://captivateiq.com/blog/compensation-benchmarking-software (13 answers)
- https://ficstar.com/best-compensation-benchmarking-data-providers-2026 (13 answers)
- https://payscale.com/ (11 answers)
- https://worldmetrics.org/service/corporate-benchmarking (11 answers)
- https://bestrecruitingtools.com/blog/best-compensation-management-software-enterprise-2026 (10 answers)

## Warned against

- Mercer: 5 of 35 labels negative. "Why you should avoid traditional providers (Mercer, Radford, Willis Towers Watson)" (GLM 4.7 FlashX, budget prompt)
- Payscale: 5 of 21 labels 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: 3 of 24 labels negative. "Providers to Avoid for "Predictable Total Cost" ... Custom pricing $15K–$80K+; participation requirements" (Kimi K2, budget prompt)
- Willis Towers Watson: 3 of 22 labels negative. "Why you should avoid traditional providers (Mercer, Radford, Willis Towers Watson)" (GLM 4.7 FlashX, budget prompt)

## Record

- Method: https://hr-ai-index.com/methodology/
- Raw judge labels and full responses: https://hr-ai-index.com/data/
- License: CC BY 4.0. Cite as HR AI Recommendation Index, September 2026 Edition, hr-ai-index.com.