| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Compensation benchmarking data | Compensation and total rewards | 5% | 7 of 148 | 50% | 28 | criticized challenger | ▲+2Since September 2026: 4% → 6%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Compensation management | Compensation and total rewards | 0% | 99 of 140 | 33% | 3 | under 10 labels · led by Pave at 18% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Pay equity | Compensation and total rewards | 0% | 46 of 73 | 0% | 1 | under 10 labels · led by Syndio at 12% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Compensation benchmarkin | 4% | 6% | ▲+2Since September 2026: 4% → 6%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 7 of 148, unchanged |
| Compensation management | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 40 → 99 of 140 |
| Pay equity | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 46 of 73, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 1 | 1 | 1 | 3 |
| Gemini 3.5 Flash | 0 | 0 | 1 | 4 | 5 |
| Perplexity Sonar | 0 | 0 | 0 | 1 | 1 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| Mistral Small | 2 | 0 | 1 | 0 | 3 |
| DeepSeek V4 Flash | 0 | 1 | 0 | 3 | 4 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 2 | 1 | 2 | 5 |
| Kimi K2 | 1 | 0 | 1 | 1 | 3 |
| GLM 4.7 FlashX | 0 | 1 | 2 | 0 | 3 |
| MiniMax M2.5 | 0 | 0 | 0 | 1 | 1 |
| GPT-6 Luna | 0 | 1 | 0 | 0 | 1 |
| Muse Glimmer 30B | 0 | 0 | 1 | 1 | 2 |
Verbatim evidence the judge attached to positive labels.
“This makes Radford a top pick for companies looking for reliable, free salary benchmarking data without a significant financial investment.” Mistral Small · Compensation benchmarkin · budget prompt · first choice
“Radford or Mercer are the top choices due to their industry-specific data and reliability” Mistral Small · Compensation benchmarkin · paraphrase prompt · first choice
“1. Radford (Aon) — *Best for B2B Tech/SaaS*” Kimi K2 · Compensation benchmarkin · paraphrase prompt · first choice
“Choose Radford if you are a large tech or life sciences company trying to understand where you stand against the market” GLM 4.7 FlashX · Pay equity · comparative prompt · alternative
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“"Why you should avoid traditional providers (Mercer, Radford, Willis Towers Watson)"” Muse Glimmer 30B · Compensation benchmarkin · negative prompt · hard negative
“without getting locked into expensive enterprise software (such as Radford, Mercer, or HRSoft) that comes with high subscription rates and steep implementation fees” Gemini 3.5 Flash · Compensation management · budget prompt · soft negative
“incredibly robust but requires manual survey participation, a higher budget, and more administrative effort than modern API-based systems” Gemini 3.5 Flash · Compensation benchmarkin · paraphrase prompt · soft negative
“$15K–$80K+/yr with mandatory survey participation. Overkill for most mid-market B2B unless you're in tech/life sciences specifically.” DeepSeek V4 Flash · Compensation benchmarkin · direct prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 87 of the 97 answers that named Radford and are not a share of its labels.
No domain is on file for Radford, so its own site is not marked.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Radford's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Radford, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Radford by email, built from the raw record of the edition. It shows: