Compensation management · October 2026 Edition
Ravio vs CompUp
One of fourteen models named Ravio first on the direct prompt; two named CompUp. Ravio was named by eleven of the fourteen models and CompUp by eight and Ravio carries 29 labels and CompUp 14, so the shares are not directly comparable.
Named in three categories this edition.
Named in three categories this edition.
First-choice share9%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#4A position in a field of 13; printed, not drawn.
Labels2914A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Ravio reading right to left. Rank and label count are printed, not drawn.Pave vs Ravio · Pave vs CompUp · Ravio vs Comprehensive
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; every quote names the model and the prompt it came from. Both figures come from the compensation management page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
RavioFirst choices, of fourteen modelsCompUp
Direct12
Paraphrase21
Comparative00
Budget-constrained12
Scale-constrained10
Negative002 against Ravio
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Ravio and CompUp 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 | | |||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B | | |
Ravio CompUp first choice named as an alternative argued againstblank: not namedEach cell is one answer, Ravio on the left and CompUp on the right.The direct prompt
The plain question, one answer per model, grouped by where Ravio and CompUp stood in it.
Ravio first, CompUp an alternative
1 of 14 modelsCompUp was named in the answer but not as the choice, or not at all.Mistral SmallRavio alternatives: CompUp, Pave, Payscale, beqom
CompUp first, Ravio not the choice
2 of 14 modelsRavio was named in the answer but not as the choice, or not at all.Llama 4 MaverickCompUp, Paylocity
MiniMax M2.5CompUp alternatives: CaptivateIQ, Figures, Paylocity, Pequity
Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Perplexity SonarCompport alternatives: CaptivateIQ, CompUp, HiBob, Payscale Ascent, Ravio
Qwen 3.7 FlashQuotaPath alternatives: Paylocity, Performio, Ravio, Visdum
Kimi K2Comprehensive alternatives: CaptivateIQ, Lattice Compensate, Pave, Ravio
GLM 4.7 FlashXPayscale Ascent alternatives: BambooHR Compensation, CompUp, Comprehensive, Figures, Lattice Compensate, Pave, Paycor, Ravio
Neither was named
7 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5HiBob alternatives: Qobra, Salary.com, Visdum, beqom
GPT-5.4 miniCaptivateIQ alternatives: Everstage, QuotaPath, Spiff
Gemini 3.5 FlashCaptivateIQ, Pave alternatives: Barley, Everstage, HiBob, QuotaPath, Salesforce Spiff
Grok 4.1 FastPaycom alternatives: Comprehensive.io, HiBob, QuotaPath, Salary.com, Visdum
DeepSeek V4 FlashComprehensive, Pave alternatives: CaptivateIQ, Lattice Compensation, Payscale Ascent
GPT-6 LunaCaptivateIQ alternatives: Lattice Compensation, Payscale, Performio, Salesforce Spiff
Muse Glimmer 30Bno first choice
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
Level: the same share of first choices.
Ravio4%#5 of 16CompUp4%#– of 16Mid-marketThe figures above
Level: the same share of first choices.
Ravio9%#2 of 13CompUp9%#4 of 13Enterprise
What the models said about Ravio
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“better suited for companies with fewer than 1,000 employees. They may become less predictable or scalable for larger organizations.” Mistral Small · negative prompt · soft negative
“Fine for small teams (<1,000 users), but avoid for enterprises” Grok 4.1 Fast · negative prompt · soft negative
“I would pick Aeqium for compensation review workflow flexibility, or Ravio if your highest priority is market benchmarking and salary banding” Perplexity Sonar · paraphrase prompt · first choice
“Ravio and CompUp are particularly strong choices if you need advanced features for complex, multi-country compensation planning” Mistral Small · paraphrase prompt · first choice
What the models said about CompUp
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“CompUp appears particularly well-suited for mid-market and enterprise organizations running complex, multi-country compensation cycles.” MiniMax M2.5 · direct prompt · first choice
Also compared
Pave vs RavioPave vs CompUpRavio vs ComprehensiveRavio vs CaptivateIQRavio vs PaycomRavio vs BambooHR CompensationRavio vs HiBobComprehensive vs CompUpCompUp vs CaptivateIQCompUp vs PaycomCompUp vs BambooHR CompensationCompUp vs HiBobAll twenty-eight head-to-head pages and the full compensation management standing
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.