Compensation benchmarking data · September 2026 Edition
Comprehensive.io vs Radford
Zero of twelve models named Comprehensive.io first on the direct prompt; zero named Radford. Comprehensive.io was named by eleven of the twelve models and Radford by eleven and Comprehensive.io carries 12 labels and Radford 27, so the shares are not directly comparable.
Named in three categories this edition.
Named in two categories this edition.
First-choice share12%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%37%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#5A position in a field of 8; printed, not drawn.
Labels1227A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Comprehensive.io reading right to left. Rank and label count are printed, not drawn.Payscale was named alongside these two in ten of the twelve direct answers. Payscale vs Comprehensive.io · Payscale vs Radford · Pave vs Comprehensive.io
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the compensation benchmarking data page.
By framing
How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Comprehensive.ioFirst choices, of twelve modelsRadford
Direct003 against Radford
Paraphrase023 against Radford
Comparative00
Budget-constrained604 against Radford
Scale-constrained00
Negative00
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.
Every model, every framing
The seventy-two answers behind the chart above, one cell each: where Comprehensive.io and Radford stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | | ||||
| MiniMax M2.5 | | |
Comprehensive.io Radford first choice named as an alternative argued againstblank: not namedEach cell is one answer, Comprehensive.io on the left and Radford on the right.The direct prompt
The plain question, one answer per model, grouped by where Comprehensive.io and Radford stood in it.
Neither was the first choice, one was named
4 of 12 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniPayscale alternatives: Radford, Salary.com
Gemini 3.5 FlashPave alternatives: Carta Total Comp, Figures, Payscale, Radford, Ravio, Salary.com
Kimi K2Payscale, SalaryCube alternatives: Mercer, Radford, Salary.com
MiniMax M2.5Payscale alternatives: Comprehensive.io
Neither was named
8 of 12 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Payscale alternatives: Lattice, SalaryCube, beqom
Perplexity SonarPayscale alternatives: Ravio, SalaryCube
Grok 4.1 FastPayscale alternatives: Pave, Salary.com
Mistral SmallSalaryCube alternatives: Pave, Payfactors, Salary.com
DeepSeek V4 FlashPayscale alternatives: ERI, Pave, Ravio, Salary.com
Llama 4 MaverickPayscale
Qwen 3.7 FlashPayscale alternatives: Pave, Payfactors, Salary.com, SalaryCube
GLM 4.7 FlashXPave alternatives: Aon Radford, CaptivateIQ, Ficstar, Mercer, OpenComp, Payscale Ascent, Ravio, Salary.com CompAnalyst
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Comprehensive.io leads by two points.
Comprehensive.io2%#6 of 10Radford0%#10 of 10Mid-marketThe figures above
Comprehensive.io leads by eight points.
Comprehensive.io12%#3 of 8Radford4%#5 of 8Enterprise
The order flips: Radford leads at enterprise.
Radford16%#2 of 10Comprehensive.io0%#– of 10What the models said about Comprehensive.io
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“three free salary benchmarking tools cover most needs at zero cost: Pave (tech roles, under 200 employees), Comprehensive.io (US tech daily data), and BLS OEWS” Claude Haiku 4.5 · budget prompt · first choice
“Free daily-refreshed tech salary data from 6,000+ U.S. companies (no participation needed) ... Great for startups/lean teams.” Grok 4.1 Fast · budget prompt · first choice
“Pave and Comprehensive.io are currently leading the market for affordable or free options” Qwen 3.7 Flash · budget prompt · first choice
What the models said about Radford
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to Avoid on a Limited Budget ... enterprise-grade pricing with far more data than most small/mid-market companies need” Kimi K2 · budget prompt · hard negative
“Avoid traditional surveys (Mercer/Radford: $10k+/year) unless scaling.” Grok 4.1 Fast · budget prompt · hard negative
“it requires active participation (submitting your own data) and can be expensive and labor-intensive to manage compared to automated tools” Gemini 3.5 Flash · paraphrase prompt · soft negative
“I'd typically recommend starting with Radford if you're in tech/SaaS, or Mercer for broader B2B sectors” Claude Haiku 4.5 · paraphrase prompt · first choice
“Mercer or Radford-style benchmark data is often the strongest foundation” GPT-5.4 mini · paraphrase prompt · first choice
“Tech-First / Specialized Platforms (Radford, Pave, CompAnalyst, Option Impact) — Best for: Scalability, ease of use, and equity/tech-heavy roles.” Qwen 3.7 Flash · scale prompt · alternative
Also compared
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.