Two of fourteen models named AWS Clean Rooms first on the direct prompt; zero named Meta Advanced Analytics. AWS Clean Rooms was named by fourteen of the fourteen models and Meta Advanced Analytics by twelve and AWS Clean Rooms carries 48 labels and Meta Advanced Analytics 26, so the shares are not directly comparable.
Named in two categories this edition.
By Meta Platforms, Menlo Park, United States, founded 2004. 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 data clean rooms page.
Across every category in the November 2026 Edition, AWS Clean Rooms and Meta Advanced Analytics were named in the same answer thirty-seven times, of the 154 answers naming AWS Clean Rooms and the 57 naming Meta Advanced Analytics. In those answers Meta Advanced Analytics took the first choice two times and AWS Clean Rooms six.
| Model | DirectACMA | ParaphraseACMA | ComparativeACMA | Budget-constrainedACMA | Scale-constrainedACMA | NegativeACMA |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | AC | AC | MA | |||
| GPT-5.4 mini | AC | AC | AC | AC | ||
| Gemini 3.5 Flash | AC | AC | AC | MA | ||
| Perplexity Sonar | AC | AC | ACMA | |||
| Grok 4.20 | AC | AC | AC | AC | MA | AC |
| Mistral Small | AC | ACMA | ||||
| DeepSeek V4 Flash | AC | AC | ACMA | ACMA | ACMA | AC |
| Llama 4 Maverick | ACMA | MA | ||||
| Qwen 3.7 Flash | AC | ACMA | ||||
| Kimi K2 | AC | AC | MA | MA | ||
| GLM 4.7 FlashX | ACMA | |||||
| MiniMax M2.5 | AC | AC | AC | |||
| GPT-6 Luna | AC | AC | AC | AC | ||
| Muse Glimmer 30B | AC | ACMA | MA |
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. Four of five in this category shown.
“AWS Clean Rooms charges for query compute, so budget for usage rather than assuming it's a free tool” GPT-6 Luna · budget prompt · soft negative
“AWS Clean Rooms or Snowflake Data Clean Rooms offer the best balance of capability, scalability, and cost-effectiveness for mid-market B2B companies” Kimi K2 · direct prompt · first choice
“Prefer neutral, interoperable platforms (like Snowflake, Databricks, AWS Clean Rooms, InfoSum, or independent providers)” DeepSeek V4 Flash · negative prompt · first choice
“Best for AWS Users: AWS Clean Rooms ... Pay-as-you-go (no upfront platform fees or monthly SaaS subscriptions)” Gemini 3.5 Flash · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to approach with caution: Native clean rooms operated by major media platforms (e.g., Google Ads Data Hub, Amazon Marketing Cloud, Meta Advanced Analytics)” Gemini 3.5 Flash · negative prompt · soft negative
“Walled Gardens: Google, Meta, Amazon—if most of your spend is there, but they limit cross-platform insights.” Grok 4.20 · scale prompt · soft negative
“Meta's history of data misuse is repeatedly cited as a reason to be cautious with its clean room offerings.” Muse Glimmer 30B · negative prompt · soft negative
“likely to be a free walled-garden option such as Google Ads Data Hub, Amazon Marketing Cloud, or Meta Advanced Analytics” Llama 4 Maverick · budget prompt · first choice
“Google, Amazon, and Meta each run a clean room that costs nothing in licence fees” Claude Haiku 4.5 · budget prompt · first choice
“Meta Advanced Analytics (currently in beta)” Mistral Small · budget 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.