A product needs 10 labels in a category before a share is stated. Mercer Benchmark Database has 3.
“Layer in: Mercer Benchmark Database — for formal job architecture and executive benchmarking as you mature”DeepSeek V4 Flash · Paraphrase question · alternative
“Highly trusted by board compensation committees and HR executives worldwide.”Gemini 3.5 Flash · Paraphrase question · alternative
“Best for Formal Job Architecture”DeepSeek V4 Flash · Direct question · alternative
No model argued against it.
The products named in the same answers as Mercer Benchmark Database, over the 6 answers that named it, and how often each was the first choice instead.
| Product | Named together | Picked instead | |
|---|---|---|---|
| 3 | 2 | View → | |
| 3 | 1 | View → | |
| 3 | 1 | View → | |
| 3 | 0 | View → | |
| 2 | 1 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → |
A side-by-side page exists where both products are among a category's top eight.
Stated on Mercer Benchmark Database's own site, not checked by Gane.
Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.
Gane sells AI visibility software. No company can pay to change a result.
Read the method →Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 5 of the 6 answers that named Mercer Benchmark Database and are not a share of its labels.
Thirty-five of the thirty-five domain citations in answers naming Mercer Benchmark Database came from a third party's page.
Pages are listed as the models cited them.
| Model | First choice | Alternative | Mention | Warning | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 0 | 1 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 2 | 0 | 0 | 2 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |