Six of fourteen models named Snowflake Data Clean Rooms first on the direct prompt; one named InfoSum. Both were named by all fourteen models and Snowflake Data Clean Rooms carries 52 labels and InfoSum 39, so the shares are not directly comparable.
By Snowflake Inc., San Mateo, United States, founded 2012. Named in one category this edition.
Named in three 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 data clean rooms page.
Across every category in the October 2026 Edition, Snowflake Data Clean Rooms and InfoSum were named in the same answer ninety times, of the 158 answers naming Snowflake Data Clean Rooms and the 119 naming InfoSum. In those answers InfoSum took the first choice six times and Snowflake Data Clean Rooms seventeen.
| 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.
“Usage-based through Snowflake consumption; costs scale with data volume” Kimi K2 · budget prompt · hard negative
“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
“Snowflake and AWS Clean Rooms get reasonable marks when properly configured — but watch for the cost/complexity pitfalls” DeepSeek V4 Flash · negative prompt · soft negative
“Choose Snowflake, Databricks, or AWS if you already have a mature data team, store most of your data in these warehouses” Gemini 3.5 Flash · comparative prompt · first choice
“Start with Snowflake Secure Data Sharing/Clean Rooms. It offers the highest probability of successful collaborations” Qwen 3.7 Flash · paraphrase prompt · first choice
“Choose Snowflake if you are a data-led organization that needs to run complex SQL queries, ensure strict data governance” GLM 4.7 FlashX · comparative 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.
“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
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.