Index › HR › Compensation and total rewards › Compensation management › Lattice Compensation vs Deel
Compensation management · November 2026 Edition
Lattice Compensation vs Deel
Zero of fourteen models named Lattice Compensation first on the direct prompt; zero named Deel. Lattice Compensation was named by fourteen of the fourteen models and Deel by nine and Lattice Compensation carries 29 labels and Deel 13, so the shares are not directly comparable.
Named in one category this edition.
Named in fifteen categories this edition.
First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 18; printed, not drawn.
Labels2913A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Lattice Compensation reading right to left. Rank and label count are printed, not drawn.Pave was named alongside these two in ten of the fourteen direct answers. Pave vs Lattice Compensation · Pave vs Deel · Aeqium vs Lattice Compensation
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.
Lattice CompensationFirst choices, of fourteen modelsDeel
Direct00
Paraphrase20
Comparative00
Budget-constrained01
Scale-constrained00
Negative00
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 Lattice Compensation and Deel 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 4.20 | | | | | ||
| 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 |
Lattice Compensation Deel first choice named as an alternative argued againstblank: not namedEach cell is one answer, Lattice Compensation on the left and Deel on the right.The direct prompt
The plain question, one answer per model, grouped by where Lattice Compensation and Deel stood in it.
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniComprehensive.io alternatives: Compport, Lattice Compensation, Paycom, Payscale Ascent, Salary.com CompAnalyst
Perplexity SonarAeqium alternatives: CaptivateIQ, Comprehensive.io, Deel, Pave
Grok 4.20Pave alternatives: Aeqium, HRSoft Compensation Management, Lattice Compensation, beqom
Kimi K2Aeqium, Pave alternatives: HRSoft Compensation Management, Lattice Compensation, beqom
MiniMax M2.5CompUp alternatives: Deel, Pave
Neither was named
9 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5no first choice
Gemini 3.5 FlashCaptivateIQ, Pave alternatives: CompLogix, Comprehensive.io, Everstage, HiBob, Rippling, Salesforce Spiff
Mistral SmallAeqium, Pave, Ravio alternatives: Compport, Decusoft Compose, HRSoft Compensation Management, beqom
DeepSeek V4 FlashPave alternatives: Aeqium, OpenComp
Llama 4 Maverickno first choice
Qwen 3.7 FlashPave alternatives: Decusoft Compose, Everstage, Payscale, QuotaPath, beqom
GLM 4.7 FlashXHRSoft Compensation Management, Pave alternatives: Aeqium, beqom
GPT-6 LunaCaptivateIQ alternatives: QuotaPath, Salesforce Spiff
Muse Glimmer 30BHRSoft Compensation Management, SalaryCube Comp Planning alternatives: CaptivateIQ, CompUp, Everstage, Pave, QuotaPath, Ravio, Salary.com CompAnalyst, beqom
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
Deel leads by four points.
Deel5%#5 of 19Lattice Compensation2%#9 of 19Mid-marketThe figures above
The order flips: Lattice Compensation leads at mid-market.
Lattice Compensation4%#4 of 18Deel2%#8 of 18Enterprise
Level: the same share of first choices.
Lattice Compensation0%#– of 17Deel0%#– of 17What the models said about Lattice Compensation
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“I recommend Pave or Lattice as top choices for salary planning and compensation review software” Grok 4.20 · paraphrase prompt · first choice
“for performance-linked pay, Lattice is ideal” Mistral Small · paraphrase prompt · first choice
“Lattice Compensation / HiBob / ChartHop: If you already use one of these for performance management or HRIS, evaluating their native compensation modules can save cost” Gemini 3.5 Flash · scale prompt · alternative
What the models said about Deel
No label in this category carried a quote.
Also compared
Pave vs Lattice CompensationPave vs DeelAeqium vs Lattice CompensationAeqium vs DeelCompUp vs Lattice CompensationCompUp vs DeelLattice Compensation vs HRSoft Compensation ManagementLattice Compensation vs CaptivateIQLattice Compensation vs QuotaPathHRSoft Compensation Management vs DeelCaptivateIQ vs DeelQuotaPath vs DeelAll 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.