# Figures vs Workleap Compensation: which do AI models recommend for pay equity, October 2026

HR AI Recommendation Index, October 2026 Edition, Pay equity. Zero of fourteen models named Figures first on the direct prompt; three named Workleap Compensation. Page: https://hr-ai-index.com/rewards/pay-equity/figures-vs-workleap-compensation/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Figures | 7% | #4 of 14 | 7% | 15 | 9 of 14 |
| Workleap Compensation | 7% | #5 of 14 | 23% | 13 | 10 of 14 |

## The direct prompt, model by model

- Claude Haiku 4.5: workleap compensation first (first choices: Workleap Compensation) (alternatives: Compport, OpenComp, PayAnalytics, Payscale, Syndio, Trusaic PayParity)
- Grok 4.1 Fast: workleap compensation first (first choices: Workleap Compensation) (alternatives: Aeqium, HiBob, Payscale)
- Llama 4 Maverick: workleap compensation first (first choices: Workleap Compensation) (alternatives: Affirmity, Effy)
- Perplexity Sonar: neither first, one named (first choices: Aeqium) (alternatives: HiBob, Payscale, Salary.com Pay Equity, Workleap Compensation)
- Mistral Small: neither first, one named (first choices: Aeqium) (alternatives: Sysarb, Workleap Compensation)
- Qwen 3.7 Flash: neither first, one named (first choices: Pave) (alternatives: Payscale, Phodata, Workleap Compensation)
- GLM 4.7 FlashX: neither first, one named (first choices: Syndio) (alternatives: Aeqium, Affirmity, Compport, Figures, HiBob, Pave, PayAnalytics, Payscale, Workday Pay Equity, beqom Pay Equity)
- MiniMax M2.5: neither first, one named (first choices: HiBob) (alternatives: Aeqium, Pave, Payscale, Workleap Compensation)
- GPT-5.4 mini: neither named (first choices: Syndio) (alternatives: PayAnalytics, Trusaic PayParity)
- Gemini 3.5 Flash: neither named (first choices: PayAnalytics) (alternatives: CandorIQ, Pequity, Syndio, Trusaic PayParity)
- DeepSeek V4 Flash: neither named (first choices: PayAnalytics) (alternatives: Compport, Payscale, Syndio)
- Kimi K2: neither named (first choices: PayAnalytics, Syndio) (alternatives: Payscale, Trusaic PayParity)
- GPT-6 Luna: neither named (first choices: Payscale) (alternatives: Syndio, Trusaic PayParity)
- Muse Glimmer 30B: neither named (first choices: PayAnalytics, beqom Pay Equity) (alternatives: Syndio, Trusaic PayParity)

## What the models said about Figures

- "Tools requiring heavy analyst intervention (e.g., certain configurations of Aeqium, Figures)" (DeepSeek V4 Flash, negative prompt, soft negative)
- "If EU-based or global: Figures offers the best balance of compliance features and usability for mid-market" (Kimi K2, paraphrase prompt, first choice)
- "I'd suggest starting with Figures or Syndio as they balance functionality with mid-market accessibility" (MiniMax M2.5, paraphrase prompt, first choice)
- "Top Recommendation: Figures HR (if EU/UK focus) or Syndio (if global/US focus)" (DeepSeek V4 Flash, paraphrase prompt, first choice)

## What the models said about Workleap Compensation

- "Lesser-known or smaller tools (e.g., Barley, Deel) may lack the depth required for enterprise-level analysis." (Mistral Small, negative prompt, hard negative)
- "Tools Lacking Enterprise Depth (e.g., smaller/low-cost options like Barley... flag them as "avoid for scale"" (Grok 4.1 Fast, negative prompt, hard negative)
- ""Avoid for your scale: Smaller tools like Barley ($5/user/month) or Deel lack enterprise depth"" (Muse Glimmer 30B, negative prompt, hard negative)
- "Barley is ideal for mid-market and enterprise HR teams needing simple compensation analytics and pay band management." (Claude Haiku 4.5, direct prompt, first choice)
- "Barley - ideal for mid-market and enterprise HR teams needing simple compensation analytics and pay band management." (Llama 4 Maverick, direct prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.