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Global payroll and employer of record · November 2026 Edition

Deel vs Rippling

Eight of fourteen models named Deel first on the direct prompt; one named Rippling. Deel was named by fourteen of the fourteen models and Rippling by thirteen and Deel carries 67 labels and Rippling 41, so the shares are not directly comparable.

Deel

accepted challenger

Named in fifteen categories this edition.

Rippling

accepted challenger

Named in thirty-three categories this edition.

First-choice share26%7%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate24%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 10; printed, not drawn.
Labels6741A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Deel reading right to left. Rank and label count are printed, not drawn.Remote was named alongside these two in thirteen of the fourteen direct answers. Deel vs Remote · Deel vs RemoFirst · Deel vs Papaya Global

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 global payroll and employer of record page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DeelFirst choices, of fourteen modelsRippling
Direct81
Paraphrase73
Comparative100
Budget-constrained006 against Deel
Scale-constrained00
Negative0010 against Deel · 3 against Rippling
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.

Across every category in the November 2026 Edition, Deel and Rippling were named in the same answer 365 times, of the 534 answers naming Deel and the 1650 naming Rippling. In those answers Rippling took the first choice sixty-seven times and Deel sixty-one.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Deel and Rippling stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Deel Rippling first choice named as an alternative argued againstblank: not namedEach cell is one answer, Deel on the left and Rippling on the right.

The direct prompt

The plain question, one answer per model, grouped by where Deel and Rippling stood in it.

Deel first, Rippling an alternative

8 of 14 modelsRippling was named in the answer but not as the choice, or not at all.
GPT-5.4 miniDeel alternatives: G-P, Multiplier, Remote, Rippling
DeepSeek V4 FlashDeel, Remote alternatives: G-P, Rippling, Velocity Global
Qwen 3.7 FlashDeel, Remote alternatives: G-P, Oyster People, Rippling
Kimi K2Deel, Remote alternatives: Multiplier, Payoneer Workforce Management, Velocity Global
GLM 4.7 FlashXDeel, Remote, Velocity Global alternatives: G-P, Multiplier
MiniMax M2.5Deel alternatives: G-P, Multiplier, Remote, Rippling, Safeguard, Velocity Global
GPT-6 LunaDeel alternatives: Remote, Rippling
Muse Glimmer 30BDeel, Remote alternatives: Omni HR, Teamed

Rippling first, Deel an alternative

1 of 14 modelsDeel was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashRippling alternatives: Deel, Papaya Global, Remote

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.
Claude Haiku 4.5Safeguard Global alternatives: Deel, Rippling, Teamed
Perplexity SonarRemote alternatives: Deel, G-P, Multiplier, Safeguard Global, Velocity Global
Grok 4.20Remote alternatives: Deel, Multiplier
Mistral SmallRemote, Teamed alternatives: Deel, G-P, Safeguard Global
Llama 4 MaverickTeamed alternatives: Atlas HXM, Deel, G-P, Remote, Velocity Global

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 thirty-five points.
Deel38%#1 of 11
Rippling4%#5 of 11
The full small business standing →
Mid-marketThe figures above
Deel leads by nineteen points.
Deel26%#1 of 10
Rippling7%#4 of 10
The full mid-market standing →
Enterprise
Deel leads by nineteen points.
Deel25%#1 of 13
Rippling6%#8 of 13
The full enterprise standing →

What the models said about Deel

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.

“Proceed with Caution (High Risk in Regulated Markets)... If they refuse to name the local entity signing the contract (common with Deel/Remote in specific sectors), avoid them” Qwen 3.7 Flash · negative prompt · hard negative
“I would advise against utilizing Deel, Remote, or similar 'new' Employer of Record (EOR) services in regions with stringent compliance requirements, such as Germany.” Muse Glimmer 30B · negative prompt · hard negative
“Deel's compliance is more risk-tolerant than many alternative platforms — and Deel's risk becomes its users' risk.” Claude Haiku 4.5 · negative prompt · hard negative
“Deel leans heavily into automation and speed, making it ideal for agile teams expanding rapidly across many jurisdictions at once.” Qwen 3.7 Flash · comparative prompt · first choice
“Deel is one of the market leaders in international employment... Choose Deel if you want the fastest global expansion tool” Gemini 3.5 Flash · comparative prompt · first choice

What the models said about Rippling

No label in this category carried a quote.

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.