Decodo vs IPRoyal
Nine of fourteen models named Decodo first on the direct prompt; zero named IPRoyal. Both were named by all fourteen models and Decodo carries 45 labels and IPRoyal 27, so the shares are not directly comparable.
Named in one category this edition.
Named in one category 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 proxy and web data providers page.
By framing
DecodoFirst choices, of fourteen modelsIPRoyal
Across every category in the October 2026 Edition, Decodo and IPRoyal were named in the same answer forty-four times, of the 107 answers naming Decodo and the 63 naming IPRoyal. In those answers IPRoyal took the first choice two times and Decodo seventeen.
Every model, every framing
| 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 | | | | |
Decodo IPRoyal first choice named as an alternative argued againstblank: not namedEach cell is one answer, Decodo on the left and IPRoyal on the right.The direct prompt
Decodo first, IPRoyal not the choice
9 of 14 modelsIPRoyal was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 of 14 modelsThe answer made no first choice from these two in this category.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
Decodo40%#1 of 9IPRoyal6%#5 of 9What the models said about Decodo
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Go with Decodo (formerly Smartproxy) if you want the best balance of price, performance, and ease of use with ISO-certified compliance.” Gemini 3.5 Flash · paraphrase prompt · first choice
“Decodo (formerly Smartproxy) - offers 115M+ IPs across 195+ countries, with a balance of enterprise capability and accessibility.” Llama 4 Maverick · direct prompt · first choice
“Oxylabs or Decodo tend to offer the best balance of reliability, support, and scalability without enterprise-level complexity” Claude Haiku 4.5 · direct prompt · first choice
What the models said about IPRoyal
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Providers with Red Flags: IPRoyal: Removed from some recommendation lists due to concerns about fake reviews and transparency issues.” Mistral Small · negative prompt · hard negative
“This provider has a strong number of severe warnings regarding deceptive marketing.” Qwen 3.7 Flash · negative prompt · hard negative
“Lower performance benchmarks (90% success rate, slower response times ~3.7s), limited city/country targeting” DeepSeek V4 Flash · comparative prompt · soft negative
“Bright Data, IPRoyal, and FloppyData are most often considered the best providers in 2025” Claude Haiku 4.5 · comparative prompt · first choice
“1. IPRoyal - Best for Very Tight Budgets ($0-100/month)” Kimi K2 · budget prompt · first choice
“IPRoyal: Affordable (34M+ ethical IPs, 40+ countries). Rotating/sticky sessions, city-level targeting. Good for small-medium use.” Grok 4.1 Fast · comparative prompt · alternative
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.