Data clean rooms for enterprise buyers
Asked as “data clean room”, and as “privacy-safe data collaboration platform”, on behalf of an enterprise B2B company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the November 2026 Edition.
Standing · first-choice share
52%
Clear leader
52Snowflake Data Clean Rooms10Decentriq06AWS Clean Rooms33others
52% of first choices, clear leader.
Since October 2026▲+14Since October 2026: 38% → 52%, +14 points. Past the 11-point floor: movement.Snowflake Data Clean Rooms held the lead, +14 points on 38%, past the floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small businessAWS Clean Rooms19%Contested▼−7Since October 2026: 26% → 19%, −7 points. Inside the 11-point floor: within noise.Standing →Mid-market
Snowflake Data Clean Rooms27%Contested▲+8Since October 2026: 19% → 27%, +8 points. Inside the 11-point floor: within noise.Standing →EnterpriseSnowflake Data Clean Rooms52%Clear leader▲+14Since October 2026: 38% → 52%, +14 points. Past the 11-point floor: movement.This page
Snowflake Data Clean Rooms27%Contested▲+8Since October 2026: 19% → 27%, +8 points. Inside the 11-point floor: within noise.Standing →EnterpriseSnowflake Data Clean Rooms52%Clear leader▲+14Since October 2026: 38% → 52%, +14 points. Past the 11-point floor: movement.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Snowflake Data Clean Rooms52%11%56endorsed leader▲+14Since October 2026: 38% → 52%, +14 points. Past the 11-point floor: movement.38% → 52%
Snowflake Data Clean Rooms52%11%56endorsed leader▲+14Since October 2026: 38% → 52%, +14 points. Past the 11-point floor: movement.38% → 52%02
Decentriq10%3%32accepted challenger▲+3Since October 2026: 7% → 10%, +3 points. Inside the 11-point floor: within noise.7% → 10%
Decentriq10%3%32accepted challenger▲+3Since October 2026: 7% → 10%, +3 points. Inside the 11-point floor: within noise.7% → 10%03AWS Clean Rooms6%14%51accepted challenger▼−5Since October 2026: 11% → 6%, −5 points. Inside the 11-point floor: within noise.11% → 6%
04
InfoSum6%3%37accepted challenger▼−5Since October 2026: 11% → 6%, −5 points. Inside the 11-point floor: within noise.11% → 6%
InfoSum6%3%37accepted challenger▼−5Since October 2026: 11% → 6%, −5 points. Inside the 11-point floor: within noise.11% → 6%05
Databricks Clean Rooms6%21%33accepted challenger▲+4Since October 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise.2% → 6%
Databricks Clean Rooms6%21%33accepted challenger▲+4Since October 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise.2% → 6%06Google BigQuery Data Clean Rooms Lab in the set4%20%15accepted challenger▲+4Since October 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise.0% → 4%
Show the five products at 0%, ordered by negative rate
11Meta Advanced Analytics0%67%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
10Amazon Marketing Cloud0%50%18criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
09Google Ads Data Hub Lab in the set0%48%21criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
08Habu0%7%14accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%
07
LiveRamp Clean Room0%6%35accepted challenger▼−9Since October 2026: 9% → 0%, −9 points. Inside the 11-point floor: within noise.9% → 0%
LiveRamp Clean Room0%6%35accepted challenger▼−9Since October 2026: 9% → 0%, −9 points. Inside the 11-point floor: within noise.9% → 0%The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. Both editions asked the same fourteen models. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
Google BigQuery Data Clean Rooms is made by Google, whose model Gemini 3.5 Flash is in the set. On the four share prompts that model made it the first choice one time of 4; the other thirteen models one time of 52. Google Ads Data Hub is made by Google, whose model Gemini 3.5 Flash is in the set. On the four share prompts that model made it the first choice zero times of 4; the other thirteen models zero times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to head
Snowflake Data Clean Rooms vs Amazon Marketing CloudSnowflake Data Clean Rooms vs Google Ads Data HubSnowflake Data Clean Rooms vs AWS Clean Rooms
Head-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.All twenty-eight head-to-head pages: the top eight products, each against each
Snowflake Data Clean Rooms vs Meta Advanced AnalyticsSnowflake Data Clean Rooms vs Databricks Clean RoomsSnowflake Data Clean Rooms vs InfoSumSnowflake Data Clean Rooms vs LiveRamp Clean RoomAmazon Marketing Cloud vs Google Ads Data HubAmazon Marketing Cloud vs AWS Clean RoomsAmazon Marketing Cloud vs Meta Advanced AnalyticsAmazon Marketing Cloud vs Databricks Clean RoomsAmazon Marketing Cloud vs InfoSumAmazon Marketing Cloud vs LiveRamp Clean RoomGoogle Ads Data Hub vs AWS Clean RoomsGoogle Ads Data Hub vs Meta Advanced AnalyticsGoogle Ads Data Hub vs Databricks Clean RoomsGoogle Ads Data Hub vs InfoSumGoogle Ads Data Hub vs LiveRamp Clean RoomAWS Clean Rooms vs Meta Advanced AnalyticsAWS Clean Rooms vs Databricks Clean RoomsAWS Clean Rooms vs InfoSumAWS Clean Rooms vs LiveRamp Clean RoomMeta Advanced Analytics vs Databricks Clean RoomsMeta Advanced Analytics vs InfoSumMeta Advanced Analytics vs LiveRamp Clean RoomDatabricks Clean Rooms vs InfoSumDatabricks Clean Rooms vs LiveRamp Clean RoomInfoSum vs LiveRamp Clean Room
One product takes 52% of first choices here, so the chart would put ten markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Three products carry a negative rate above 25% in this category.
What they warned about
Four of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Gemini 3.5 Flash, Perplexity Sonar, Mistral Small, Llama 4 Maverick, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5 and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Meta Advanced Analytics
67%
8 of 12 labels negative · 8 of 14 models · 5 hard negative
“Walled Garden DCRs (e.g., Google Ads Data Hub/ADH, Meta Advanced Analytics, Amazon Marketing Cloud/AMC)... Avoid if your needs involve multi-party/cross-platform analysis” Grok 4.20, negative prompt
Amazon Marketing Cloud
50%
9 of 18 labels negative · 7 of 14 models · 5 hard negative
“Walled Garden DCRs (e.g., Google Ads Data Hub/ADH, Meta Advanced Analytics, Amazon Marketing Cloud/AMC)... Avoid if your needs involve multi-party/cross-platform analysis” Grok 4.20, negative prompt
Google Ads Data Hub
48%
10 of 21 labels negative · 6 of 14 models · 5 hard negative
“Walled Garden DCRs (e.g., Google Ads Data Hub/ADH, Meta Advanced Analytics, Amazon Marketing Cloud/AMC)... Avoid if your needs involve multi-party/cross-platform analysis” Grok 4.20, negative prompt
AWS Clean Rooms
14%
7 of 51 labels negative · 5 of 14 models · 3 hard negative
“Options to Avoid for Predictability - AWS Clean Rooms: Explicitly flagged ... as one to avoid for predictable costs” MiniMax M2.5, budget prompt
What they cite
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted.
Sites the answers cite
77 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 1002 links across 275 sites, every framing counted. Ranked by the number of answers carrying the site or page. 74 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
vendor site · Decentriq39 answers · 55 citations · 13 models
vendor site · LiveRamp34 answers · 51 citations · 13 models
publisher (Gane)30 answers · 31 citations · 9 models
vendor site · Snowflake26 answers · 40 citations · 11 models
vendor site · Snowflake25 answers · 40 citations · 10 models
vendor site · Amazon Web Services23 answers · 37 citations · 11 models
21 answers · 26 citations · 9 models
vendor site · Forrester18 answers · 21 citations · 7 models
17 answers · 17 citations · 11 models
16 answers · 16 citations · 9 models
vendor site · Databricks13 answers · 20 citations · 8 models
vendor site · Guideflow12 answers · 12 citations · 7 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
29 answers · 9 models
27 answers · 10 models
24 answers · 12 models
17 answers · 11 models
16 answers · 9 models
16 answers · 9 models
15 answers · 7 models
14 answers · 9 models
13 answers · 7 models
12 answers · 7 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best data clean room”, “data clean room”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Snowflake Data Cloud snowflake.com Snowflake Data Clean Rooms 52% | 52% | 158 | 390 | 11 | 718,749 company | 118 | 6 | |
| Decentriq decentriq.com | 10% | 71 | 170 | 1 | 911 | 2 | ||
| AWS Clean Rooms | 6% | 720 | 4 | |||||
| InfoSum infosum.com | 6% | 95 | 390 | 7 | 362 | 5 | 6 | |
| Databricks databricks.com Databricks Clean Rooms 6% | 6% | 66 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 | 3 |
| Microsoft parent site Microsoft Teams 4%, Microsoft 365 2% | 6% | 95 | 2,240,000 | 403,136 | ||||
| Google parent site Google BigQuery Data Clean Rooms 4% | 4% | 37 | ||||||
| DataMoon Clean Room datamoon.com | 2% | 5 | ||||||
| Nextcloud nextcloud.com | 2% | 3 | ||||||
| Omnisient omnisient.com | 2% | 2 |
Google's top ten for the two searches hold 16 sites; 4 of them are among the sites the models cited here (databricks.com, decentriq.com, liveramp.com, snowflake.com). The first result for “best data clean room” is gartner.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best data clean room for an enterprise B2B company?”Paraphrase“Which privacy-safe data collaboration platform would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade data clean rooms and how do they differ?”Budget-constrained“What is the best data clean room for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a data clean room. What should we look at?”Negative“Which data clean rooms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5no first choiceMicrosoft 365, Microsoft TeamsChangedSnowflake Data Clean RoomsSnowflake Data Clean Roomsno first choicenothing named
Five alternatives
AWS Clean Rooms, Databricks Clean Rooms, Decentriq, LiveRamp Clean Room, Snowflake Data Clean RoomsFour alternatives
Box, Duality Technologies, Google Workspace, KiteworksTwo alternatives
Habu, Microsoft Azure Clean RoomsTwo alternatives
AWS Clean Rooms, Databricks Clean RoomsGPT-5.4 miniSnowflake Data Clean RoomsSnowflake Data Clean RoomsHeldLiveRamp Clean RoomSnowflake Data Clean Roomsagainst: AWS Clean Roomsno first choiceagainst: AWS Clean Rooms, Google's BigQuery clean room, Salesforce clean room
Three alternatives
AWS Clean Rooms, Azure Databricks Clean Rooms, Google BigQuery Data Clean RoomsTwo alternatives
Databricks Clean Rooms, LiveRamp Safe HavenEight alternatives
AWS Clean Rooms, Amazon Marketing Cloud, Decentriq, Google Ads Data Hub, Habu, InfoSum, Optable, Snowflake Data Clean RoomsOne alternative
Ads Data HubGemini 3.5 FlashSnowflake Data Clean RoomsInfoSumChangedAWS Clean Rooms, Snowflake Data Clean RoomsGoogle BigQuery Data Clean RoomsAWS Clean Rooms, Databricks Clean Rooms, Snowflake Data Clean Roomsagainst: Amazon Marketing Cloud, Google Ads Data Hub, Meta Advanced Analytics
Five alternatives
AWS Clean Rooms, Databricks Clean Rooms, Decentriq, InfoSum, LiveRamp Clean RoomFour alternatives
Databricks Clean Rooms, Decentriq, LiveRamp Clean Room, Snowflake Data Clean RoomsFour alternatives
Databricks Clean Rooms, Decentriq, InfoSum, LiveRamp Clean RoomThree alternatives
InfoSum, LiveRamp Clean Room, Snowflake Data Clean RoomsThree alternatives
Habu, InfoSum, LiveRamp Clean RoomPerplexity SonarSnowflake Data Clean RoomsDecentriqChangedSnowflake Data Clean RoomsSnowflake Data Clean Roomsno first choiceagainst: AWS, Amazon, Databricks Clean Rooms, Google, Google BigQuery Data Clean Rooms, Meta Advanced Analytics, Snowflake Data Clean Rooms
Two alternatives
AWS Clean Rooms, DecentriqThree alternatives
Box, Kiteworks, Microsoft 365Seven alternatives
AWS Clean Rooms, Amazon Marketing Cloud, Databricks Clean Rooms, Decentriq, Google Ads Data Hub, InfoSum, LiveRamp Clean RoomFour alternatives
AWS Clean Rooms, Decentriq, InfoSum, LiveRamp Clean RoomGrok 4.20Snowflake Data Clean RoomsSnowflake Data Clean RoomsHeldagainst: Box, Microsoft Purview, SlackLiveRamp Safe HavenSnowflake Data Clean Roomsagainst: Ads Data Hub, Databricks Clean Rooms, Google BigQuery Data Clean RoomsSnowflake Data Clean Roomsagainst: AWS, Amazon Marketing Cloud, Databricks Clean Rooms, Google Ads Data Hub, Meta Advanced Analytics
Two alternatives
AWS Clean Rooms, Google BigQuery Data Clean RoomsTwo alternatives
AWS Clean Rooms, Databricks Clean RoomsFive alternatives
AWS Clean Rooms, Amazon Marketing Cloud, Google Ads Data Hub, InfoSum, Snowflake Data Clean RoomsTwo alternatives
AWS Clean Rooms, LiveRamp Clean RoomTwo alternatives
Decentriq, LiveRamp Safe HavenMistral SmallSnowflake Data Clean RoomsOmnisientChangedno first choiceGoogle BigQuery Data Clean Roomsno first choiceagainst: Amazon, Google, Meta Advanced Analytics
Two alternatives
AWS Clean Rooms, InfoSumTwo alternatives
AppsFlyer, OneTrustTwo alternatives
AWS Clean Rooms, Snowflake Data Clean RoomsDeepSeek V4 FlashSnowflake Data Clean RoomsSnowflake Data Clean RoomsHeldno first choiceagainst: Amazon Marketing Cloud, Google Ads Data HubSnowflake Data Clean Roomsagainst: AWS Clean Rooms, Databricks Clean Rooms, Google Ads Data Hubno first choiceagainst: AWS Clean Rooms, Amazon Marketing Cloud, Databricks Clean Rooms, Decentriq, Disney's and NBCUniversal's clean rooms, Google Ads Data Hub, Habu, InfoSum, LiveRamp Safe Haven, Meta Advanced Analytics, Snowflake Data Clean Rooms
Two alternatives
AWS Clean Rooms, LiveRamp Clean RoomFour alternatives
AWS Clean Rooms, Databricks Clean Rooms, Habu, InfoSumSix alternatives
AWS Clean Rooms, Databricks Clean Rooms, Decentriq, InfoSum, LiveRamp Clean Room, Snowflake Data Clean RoomsTwo alternatives
Decentriq, LiveRamp Clean RoomLlama 4 MaverickSnowflake Data Clean RoomsDataMoon Clean RoomChangedno first choiceAWS Clean Rooms, Databricks Clean Rooms, Snowflake Data Clean Roomsno first choicenothing named
Four alternatives
Duality Technologies, OneTrust, Proton Drive, idgardOne alternative
Google BigQuery Data Clean RoomsQwen 3.7 FlashSnowflake Data Clean RoomsDecentriq, Snowflake Data Marketplace / Snowflake Private ListingChangedLiveRamp Clean RoomSnowflake Data Clean Roomsagainst: Adobe, LiveRamp Clean Roomno first choiceagainst: Amazon Marketing Cloud, Google DV360 Clean Rooms, LiveRamp Clean Room, Meta Advanced Analytics, Tealium
Two alternatives
Crossbeam, LiveRamp Clean RoomSix alternatives
Box, LiveRamp Clean Room, Mattermost, Microsoft Purview, ONES.com, OnBaseSix alternatives
Amazon Advertising (AMA) Clean Rooms, Meta (Facebook) Advantage+ Audience Match, Microsoft Commercial Cloud, Neustar, Salesforce Data 360 Clean Rooms, TikTok Data Clean RoomsOne alternative
AWS Clean RoomsKimi K2Snowflake Data Clean RoomsNextcloud, TresoritChangedno first choiceInfoSumagainst: AWS Clean Rooms, Databricks Clean Rooms, Snowflake Data Clean Roomsno first choiceagainst: Snowflake Data Clean Rooms
Three alternatives
AWS Clean Rooms, InfoSum, LiveRamp Clean RoomTwo alternatives
Decentriq, InfoSumTwo alternatives
Decentriq, LiveRamp Clean RoomGLM 4.7 FlashXSnowflake Data Clean RoomsDecentriqChangedno first choiceagainst: Microsoft Advertising Data Clean RoomSnowflake Data Clean Roomsno first choiceagainst: Amazon Marketing Cloud, Google Ads Data Hub, Meta Advanced Analytics
Four alternatives
AWS Clean Rooms, Databricks Clean Rooms, InfoSum, LiveRamp Clean RoomThree alternatives
DataMoon Clean Room, Duality, PartnerTapFive alternatives
AWS Clean Rooms, Databricks Clean Rooms, Google Ads Data Hub, LiveRamp Clean Room, Snowflake Data Clean RoomsThree alternatives
AWS Clean Rooms, InfoSum, LiveRamp Clean RoomMiniMax M2.5InfoSumMicrosoft Teams, WireChangedno first choiceDecentriqagainst: AWS Clean Rooms, Snowflake Data Clean Roomsno first choicenothing named
Six alternatives
AWS Clean Rooms, Google Cloud's Ads Data Hub & BigQuery Clean Rooms, Habrick, LiveRamp (now part of TransUnion) - Safe Haven, Microsoft Azure's Clean Room, Snowflake's Clean RoomsTwo alternatives
AWS Clean Rooms, idgardEight alternatives
AWS Clean Rooms, Amazon Marketing Cloud, Databricks Clean Rooms, Decentriq, Google Ads Data Hub, InfoSum, LiveRamp Clean Room, Snowflake Data Clean RoomsTwo alternatives
Databricks Clean Rooms, LiveRamp Clean RoomGPT-6 LunaSnowflake Data Clean RoomsSnowflake Data Clean RoomsHeldAWS Clean Rooms, Snowflake Data Clean Roomsagainst: Amazon Marketing Cloud, Google Ads Data HubAWS Clean Roomsno first choiceagainst: Amazon Marketing Cloud, Google Ads Data Hub, Google BigQuery Data Clean Rooms
Three alternatives
AWS Clean Rooms, Databricks Clean Rooms, LiveRamp Clean RoomThree alternatives
AWS Clean Rooms, Databricks Clean Rooms, InfoSumFive alternatives
Databricks Clean Rooms, Decentriq, Google BigQuery Data Clean Rooms, InfoSum, LiveRamp Clean RoomTwo alternatives
Google BigQuery Data Clean Rooms, Snowflake Data Clean RoomsMuse Glimmer 30BSnowflake Data Clean RoomsDatabricks Clean Rooms, Snowflake Data Clean RoomsChangedAWS Clean Rooms, Snowflake Data Clean Roomsagainst: Amazon AMC, Google Ads Data Hub, Meta Advanced Analytics, TikTok PrivacyGoDecentriqagainst: AWS Clean Rooms, Databricks Clean Rooms, Snowflake Data Clean Roomsno first choiceagainst: Amazon Marketing Cloud, Google Ads Data Hub
One alternative
CrossbeamThree alternatives
Box, Nextcloud, OmnisientThree alternatives
Google BigQuery Data Clean Rooms, InfoSum, LiveRamp Clean RoomBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:25 | yes | 9 | 6 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 15:23 | yes | 4 | 8 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 15:11 | yes | 3 | 22 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 16:08 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:34 | yes | 10 | 12 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:42 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 09:20 | yes | 23 | 22 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:53 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 16:42 | yes | 9 | 51 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:08 | yes | 20 | 44 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:54 | yes | 23 | 76 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:07 | no | 0 | 35 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:03 | yes | 4 | 16 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 13:43 | yes | 12 | 19 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:39 | yes | 17 | 10 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 15:55 | yes | 4 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 16:23 | no | 0 | 15 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 13:00 | yes | 10 | 3 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:54 | yes | 10 | 10 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 08:50 | yes | 5 | 3 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:57 | yes | 25 | 21 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:55 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:00 | yes | 10 | 40 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 11:30 | yes | 20 | 33 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:51 | yes | 21 | 60 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:22 | yes | 10 | 23 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:36 | yes | 4 | 16 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:35 | yes | 15 | 18 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 16:36 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:27 | yes | 7 | 8 s |
| Comparative | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 14:39 | yes | 8 | 26 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 16:02 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:15 | yes | 14 | 17 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:53 | yes | 15 | 12 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:42 | yes | 24 | 40 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:58 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:33 | no | 0 | 33 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:43 | yes | 24 | 33 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:47 | yes | 24 | 279 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:30 | yes | 16 | 33 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:42 | yes | 9 | 27 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 10:07 | yes | 13 | 29 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:01 | yes | 19 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 15:26 | yes | 5 | 14 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 09:53 | no | 0 | 18 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 09:20 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:50 | yes | 10 | 12 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 14:44 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:00 | yes | 24 | 31 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:16 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:33 | yes | 8 | 76 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:17 | yes | 24 | 96 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:06 | yes | 24 | 22 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:36 | yes | 22 | 82 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:42 | yes | 2 | 19 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:28 | yes | 23 | 29 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:32 | yes | 27 | 14 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:40 | yes | 7 | 9 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 15:17 | no | 0 | 20 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 11:00 | yes | 10 | 9 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:36 | yes | 10 | 14 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 16:14 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 17:07 | yes | 25 | 51 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:38 | yes | 5 | 4 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:00 | yes | 10 | 32 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:03 | yes | 15 | 31 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 16:03 | yes | 21 | 210 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 11:01 | no | 0 | 22 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:05 | yes | 6 | 26 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 16:55 | yes | 17 | 26 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 16:49 | yes | 19 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 10:54 | yes | 5 | 11 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 11:39 | yes | 7 | 32 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 11:07 | yes | 10 | 6 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:39 | yes | 17 | 15 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 13:29 | yes | 5 | 3 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 08:33 | yes | 25 | 33 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 15:03 | yes | 5 | 4 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:24 | yes | 15 | 36 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 16:15 | yes | 20 | 62 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 15:28 | yes | 25 | 23 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:39 | yes | 18 | 64 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 08:57 | yes | 5 | 19 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:02 | yes | 21 | 29 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
BigQuery read as Google BigQuery Data Clean Rooms
Databricks read as Databricks Clean Rooms
Databricks Data Clean Rooms read as Databricks Clean Rooms
Google ADH read as Google Ads Data Hub
Google Cloud BigQuery read as Google BigQuery Data Clean Rooms
Google Cloud BigQuery Clean Rooms read as Google BigQuery Data Clean Rooms
Google Cloud BigQuery Data Clean Rooms read as Google BigQuery Data Clean Rooms
LiveRamp read as LiveRamp Clean Room
LiveRamp (ActiveView) read as LiveRamp Clean Room
LiveRamp (Habu) read as LiveRamp Clean Room
LiveRamp (LiveRamp Collaboration Solutions) read as LiveRamp Clean Room
LiveRamp (Relativity Data) read as LiveRamp Clean Room
LiveRamp (Safe Haven) read as LiveRamp Clean Room
LiveRamp (powered by Habu) read as LiveRamp Clean Room
Meta read as Meta Advanced Analytics
Meta (Facebook) Advanced Analytics Clean Room read as Meta Advanced Analytics
Meta AA read as Meta Advanced Analytics
Meta Clean Room (formerly Glimpse) read as Meta Advanced Analytics
Salesforce (Einstein CDP Clean Rooms) read as Salesforce Data 360 Clean Rooms
Snowflake read as Snowflake Data Clean Rooms
Snowflake Data Clean Room read as Snowflake Data Clean Rooms
Snowflake Data Cloud read as Snowflake Data Clean Rooms
Unresolved, counted raw
Adobe
Amazon Advertising (AMA) Clean Rooms
AppsFlyer Data Collaboration Platform
Azure Databricks Clean Rooms
Azure Synapse Dedicated Pool
Databricks Cleanrooms
Databricks Delta Share
Disney's and NBCUniversal's clean rooms
Google
Google Cloud's Ads Data Hub & BigQuery Clean Rooms
Google DV360 Clean Rooms
Google's BigQuery clean room
Habrick (formerly Decentri)
LiveRamp (now part of TransUnion) - Safe Haven
Meta (Facebook) Advantage+ Audience Match
Meta equivalents
Microsoft Advertising Data Clean Room (MAP)
Microsoft Azure's Clean Room (Powered by OneLake)
Microsoft Commercial Cloud (DART)
Microsoft's clean room
Microsoft’s offerings
OnBase (Hyland)
Privacy Analytics
Salesforce clean room
Snowflake Data Marketplace / Snowflake Private Listing
Snowflake's Clean Rooms
The Trade Desk Galileo
TikTok Data Clean Rooms
WPP/GroupM
Discontinued, still offered
No shut-down product was recommended here.