CookieYes vs Ketch
Zero of fourteen models named CookieYes first on the direct prompt; zero named Ketch. CookieYes was named by thirteen of the fourteen models and Ketch by thirteen and CookieYes carries 37 labels and Ketch 33, 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 consent and privacy management page.
By framing
CookieYesFirst choices, of fourteen modelsKetch
Across every category in the November 2026 Edition, CookieYes and Ketch were named in the same answer thirty times, of the 103 answers naming CookieYes and the 87 naming Ketch. In those answers Ketch took the first choice one time and CookieYes four.
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 4.20 | | | | | | |
| 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 | | |
CookieYes Ketch first choice named as an alternative argued againstblank: not namedEach cell is one answer, CookieYes on the left and Ketch on the right.The direct prompt
Neither was the first choice, one was named
8 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
6 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
CookieYes30%#1 of 11Ketch0%#– of 11CookieYes16%#4 of 13Ketch2%#7 of 13Ketch8%#2 of 9CookieYes0%#– of 9What the models said about CookieYes
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Too basic; built for small businesses and WordPress sites. Lacks DSAR, vendor governance” Kimi K2 · direct prompt · hard negative
“Frequent complaints about poor/slow customer support, bureaucratic processes, high costs” Grok 4.20 · negative prompt · hard negative
“tools such as CookieYes may be fine for basic sites, but check support for GPC, IAB GPP, Google Consent Mode, TCF, multilingual regional rules” Perplexity Sonar · negative prompt · soft negative
“CookieYes is frequently recommended as the best overall budget choice.” Claude Haiku 4.5 · budget prompt · first choice
“the best default choice is usually CookieYes. It has a free plan” GPT-5.4 mini · budget prompt · first choice
“For a small company managing website cookies, I'd start with CookieYes.” GPT-6 Luna · budget prompt · first choice
What the models said about Ketch
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“its market share and user preference have declined significantly (from 24% to 10% in recent evaluations), and it has faced criticism for not being as user-friendly or effective as competitors” Mistral Small · negative prompt · soft negative
“I recommend Ketch or Cookiebot by Usercentrics as the top cookie consent and privacy compliance tools” Mistral Small · paraphrase prompt · first choice
“Ketch is API-first CMP that handles consent propagation to downstream systems like Salesforce through API-driven architecture” Claude Haiku 4.5 · comparative prompt · alternative
“Choose Ketch when consent must be enforced consistently across backend systems” Perplexity Sonar · 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.