One of fourteen models named InfoSum first on the direct prompt; one named Databricks Clean Rooms. InfoSum was named by fourteen of the fourteen models and Databricks Clean Rooms by twelve and InfoSum carries 39 labels and Databricks Clean Rooms 27, so the shares are not directly comparable.
Named in three categories this edition.
By Databricks, San Francisco, United States, founded 2013. 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 October 2026 Edition, InfoSum and Databricks Clean Rooms were named in the same answer forty-six times, of the 119 answers naming InfoSum and the 73 naming Databricks Clean Rooms. In those answers Databricks Clean Rooms took the first choice one time and InfoSum one.
| 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.
“Avoid enterprise SaaS (e.g., LiveRamp, InfoSum) at $500+/month unless trialing.” Grok 4.1 Fast · budget prompt · hard negative
“pricing and complexity are often overkill for mid-market needs” DeepSeek V4 Flash · direct prompt · hard negative
“like LiveRamp (Habu), InfoSum, or Decentriq is rarely feasible, as licensing fees for these platforms often run in the tens or hundreds of thousands of dollars annually” Gemini 3.5 Flash · budget prompt · soft negative
“InfoSum – Praised for its flexible collaboration capabilities and suitability for mid-market needs, without requiring enterprise-scale resources.” Mistral Small · direct prompt · first choice
“I would recommend InfoSum as a privacy-safe data collaboration platform for a mid-sized B2B company.” Llama 4 Maverick · paraphrase prompt · first choice
“I would recommend InfoSum if your priority is privacy-safe data collaboration with partners” Perplexity Sonar · paraphrase 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.
“Cloud-based (e.g., AWS Clean Rooms, Snowflake, Databricks) | Strong infrastructure, but integration complexity and variable TCO” Grok 4.1 Fast · negative prompt · soft negative
“Some concerns about identity resolution rules not being well-documented” Kimi K2 · negative prompt · soft negative
“user reviews of Databricks Clean Rooms have scored poorly here” DeepSeek V4 Flash · negative prompt · soft negative
“Snowflake, Databricks, and LiveRamp Safe Haven provide balanced scalability and governance support.” Claude Haiku 4.5 · direct prompt · first choice
“Choose Snowflake, Databricks, or AWS if you already have a mature data team” Gemini 3.5 Flash · comparative prompt · first choice
“If your data ecosystem is built on Databricks, their Delta Sharing and Unity Catalog offer a similar, highly secure distributed data clean room experience.” Gemini 3.5 Flash · paraphrase 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.