Eleven of fourteen models named Deel first on the direct prompt; one named Papaya Global. Both were named by all fourteen models and Deel carries 64 labels and Papaya Global 42, so the shares are not directly comparable.
Named in seventeen categories this edition.
Named in four categories this edition.
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.
Across every category in the October 2026 Edition, Deel and Papaya Global were named in the same answer 129 times, of the 543 answers naming Deel and the 159 naming Papaya Global. In those answers Papaya Global took the first choice ten times and Deel thirty-nine.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Highest Caution: Active Legal/Ethical Controversies ... Rippling sued Deel alleging corporate espionage” Kimi K2 · negative prompt · hard negative
“Deel dominates the freelancer space but faces scrutiny regarding its EOR services for full-time employees... "billing shocks"...Avoid If: You need flexible, human-negotiated contract terms” Qwen 3.7 Flash · negative prompt · soft negative
“I would put Deel in the "do extra diligence" bucket\u2014not because there's established evidence here of payroll failures, but because of its unusually contentious, ongoing litigation” GPT-6 Luna · negative prompt · soft negative
“repeatedly ranked among the leading EOR providers; it is described as strong for global hiring, compliance, payroll support, and centralized workforce management” Perplexity Sonar · comparative prompt · first choice
“Deel – Best Overall ... If you want the best overall solution: Deel offers the most mature platform with the widest feature set.” Kimi K2 · direct prompt · first choice
“Covers 150+ countries; strong in scalability, contractor management, and compliance. Often top-rated for speed and global reach.” Grok 4.1 Fast · comparative prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.
“Papaya Global: Repeated issues with payroll delays, tax filing errors, and poor support response times in complex markets” Grok 4.1 Fast · negative prompt · hard negative
“Avoid Papaya Global unless you have a dedicated compliance person reviewing every payroll cycle manually.” DeepSeek V4 Flash · negative prompt · hard negative
“Implementation runs 8-12 weeks in complex environments... EOR delivered via in-country partners, so service quality varies by market” Muse Glimmer 30B · negative prompt · soft negative
“Papaya is widely considered the leading global payments and payroll platform... Choose Papaya Global if you want the most powerful technology” Qwen 3.7 Flash · paraphrase prompt · first choice
“or Papaya Global if you're scaling internationally and need deeper financial controls. Both are built for your company size” Kimi K2 · paraphrase prompt · first choice
“the best global payroll provider for a mid-sized B2B company would be Papaya Global” Llama 4 Maverick · paraphrase prompt · first choice
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.