Data warehouses
Asked as “cloud data warehouse”, and as “analytical data warehouse platform”, on behalf of a mid-market B2B company. 51 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
49%
Clear leader
49Snowflake47Google BigQuery02Amazon Redshift02others
49% of first choices, clear leader.
Since September 2026↗new leaderNew leader since September 2026: Google BigQuery (48%) replaces Snowflake (47% then, 48% now), 0 points clear, inside the 11-point floor.Google BigQuery leads at 48%, replacing Snowflake, which led at 47% and stands at 48% now: 0 points clear, inside the floor, so the swap reads as unsettled.
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 business
Google BigQuery63%Clear leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →Mid-market
Snowflake49%Clear leader↗new leaderNew leader since September 2026: Google BigQuery (48%) replaces Snowflake (47% then, 48% now), 0 points clear, inside the 11-point floor.This pageEnterpriseSnowflake62%Clear leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →
Google BigQuery63%Clear leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →Mid-marketSnowflake49%Clear leader↗new leaderNew leader since September 2026: Google BigQuery (48%) replaces Snowflake (47% then, 48% now), 0 points clear, inside the 11-point floor.This pageEnterpriseSnowflake62%Clear leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →The standing
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. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01Snowflake49%22%78endorsed leader▲+1Since September 2026: 47% → 48%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.47% → 48%
Snowflake49%22%78endorsed leader▲+1Since September 2026: 47% → 48%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.47% → 48%02Google BigQuery Lab in the set47%16%80endorsed leader▲+3Since September 2026: 44% → 48%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.44% → 48%
Google BigQuery Lab in the set47%16%80endorsed leader▲+3Since September 2026: 44% → 48%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.44% → 48%03
Amazon Redshift2%16%80accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Amazon Redshift2%16%80accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%04
ClickHouse Cloud2%12%25accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%
ClickHouse Cloud2%12%25accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%Show the four products at 0%, ordered by negative rate
08Azure Synapse Analytics0%22%27accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
06Microsoft Fabric Data Warehouse0%13%23accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
05
Databricks SQL0%12%41accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Databricks SQL0%12%41accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%07
MotherDuck0%8%13accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
MotherDuck0%8%13accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 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 is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. 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 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 two times of 4; the other thirteen models twenty-two times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
All six head-to-head pages: the top four products, each against each
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405M06
07A08
Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01Snowflake49%
Snowflake49%02Google BigQuery47%
Google BigQuery47%03Amazon Redshift2%
Amazon Redshift2%04ClickHouse Cloud2%
ClickHouse Cloud2%05Databricks SQL0%
Databricks SQL0%06Microsoft Fabric Data Warehouse0%
07MotherDuck0%
MotherDuck0%08Azure Synapse Analytics0%
What they warned about
Nine of fourteen models held their first choice under the paraphrase. DeepSeek V4 Flash, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX 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.
Amazon Redshift16%
13 of 80 labels negative · 13 of 14 models · 1 hard negative
“Why avoid it: In a provisioned Redshift environment, you pay for the nodes 24/7 regardless of whether you are querying them.” Gemini 3.5 Flash, negative prompt
Google BigQuery16%
13 of 80 labels negative · 13 of 14 models
“On-demand charges are based on data processed... configure controls—or compare capacity pricing—before opening it up to lots of users.” GPT-6 Luna, negative prompt
Snowflake22%
17 of 78 labels negative · 11 of 14 models · 2 hard negative
“What to Avoid on a Tight Budget - **Snowflake**: ... It's typically the most expensive option.” DeepSeek V4 Flash, budget prompt
Azure Synapse Analytics
22%
6 of 27 labels negative · 6 of 14 models · 3 hard negative
“Why avoid it: Building a new 3-to-5-year data architecture on Synapse dedicated pools today means you will be forced to undergo a complex migration to Fabric” Gemini 3.5 Flash, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
73 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. 959 links across 236 sites, every framing counted. Ranked by the number of answers carrying the site or page. 5 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 · OvalEdge41 answers · 41 citations · 11 models
39 answers · 60 citations · 12 models
31 answers · 31 citations · 12 models
vendor site · Fivetran25 answers · 30 citations · 9 models
vendor site · Atlan21 answers · 21 citations · 9 models
18 answers · 20 citations · 10 models
17 answers · 22 citations · 9 models
16 answers · 21 citations · 7 models
vendor site · Airbyte16 answers · 16 citations · 8 models
vendor site · Tinybird15 answers · 16 citations · 9 models
vendor site · MotherDuck14 answers · 18 citations · 8 models
14 answers · 14 citations · 8 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.
41 answers · 11 models
32 answers · 12 models
31 answers · 12 models
21 answers · 9 models
21 answers · 9 models
15 answers · 7 models
15 answers · 8 models
15 answers · 9 models
14 answers · 9 models
13 answers · 8 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 cloud data warehouse”, “cloud data warehouse”, “cloud data warehouses”. 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 snowflake.com | 49% | 228 | 368,000 | 37,077 | 718,749 | 118 | ||
| Google BigQuery cloud.google.com | 47% | 224 | 8,100 | 359 | 7,405,347 | |||
| Amazon aws.amazon.com Amazon Redshift 2%, Amazon Athena 0% | 2% | 198 | 151,000,000 | 1,380,939 | 9,238,321 | $20,476 | ||
| ClickHouse Cloud clickhouse.com | 2% | 178 | 1,000 | 15 | 43,805 | 47 | 3 | |
| Databricks databricks.com Databricks SQL 0% | 0% | 103 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 | 6 |
| Microsoft parent site Microsoft Fabric Data Warehouse 0% | 0% | 49 | 2,240,000 | 403,136 | ||||
| MotherDuck motherduck.com | 0% | 42 | 5,400 | 66 | 22,212 | 30 | ||
| Azure Synapse Analytics | 0% | 301,000 | 47,904 | |||||
| Azure parent site Azure SQL Database 0% | 0% | 147 | 301,000 | 47,904 | ||||
| DuckDB duckdb.org | 0% | 14 | 18,100 | 686 | 15,468 |
Google's top ten for the three searches hold 21 sites; 3 of them are among the sites the models cited here (clickhouse.com, fortegrp.com, scnsoft.com). The first result for “best cloud data warehouse” is reddit.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 cloud data warehouse for a mid-market B2B company?”Paraphrase“Which analytical data warehouse platform would you recommend to a mid-sized B2B company?”Comparative“What are the top cloud data warehouses and how do they differ?”Budget-constrained“What is the best cloud data warehouse for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a cloud data warehouse. What should we look at?”Negative“Which cloud data warehouses should I avoid or be cautious about?”
Claude Haiku 4.5SnowflakeSnowflakeHeldno first choiceClickHouse Cloudno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Four alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, Google BigQueryFive alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, MotherDuck, PanoplyGPT-5.4 miniSnowflakeSnowflakeHeldGoogle BigQuery, SnowflakeGoogle BigQueryno first choicenothing named
Three alternatives
Amazon Redshift, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, Azure Synapse AnalyticsTwo alternatives
PostgreSQL, SnowflakeGemini 3.5 FlashSnowflakeSnowflakeHeldno first choiceGoogle BigQueryagainst: SnowflakeGoogle BigQuery, Snowflakeagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Oracle Autonomous Data Warehouse, Snowflake, Teradata Vantage
Four alternatives
Amazon Redshift, Google BigQuery, Microsoft Fabric Data Warehouse, MotherDuckThree alternatives
Google BigQuery, Microsoft Fabric Data Warehouse, MotherDuckFour alternatives
Amazon Athena, ClickHouse Cloud, DuckDB, MotherDuckOne alternative
Amazon RedshiftPerplexity SonarSnowflakeSnowflakeHeldSnowflakeGoogle BigQueryno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Three alternatives
Azure SQL Database, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Azure SQL Database, ClickHouse Cloud, IBM Db2 WarehouseFour alternatives
Amazon Redshift, ClickHouse Cloud, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, ClickHouse CloudGrok 4.1 FastGoogle BigQueryGoogle BigQueryHeldno first choiceGoogle BigQueryagainst: SnowflakeSnowflakeagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, SnowflakeThree alternatives
Amazon Redshift, Databricks SQL, SnowflakeOne alternative
Amazon RedshiftFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryMistral SmallSnowflakeSnowflakeHeldno first choiceGoogle BigQueryno first choiceagainst: Synapse Analyticsagainst: Amazon Redshift, Azure Synapse Analytics, ClickHouse Cloud, Databricks SQL, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQueryOne alternative
Amazon RedshiftDeepSeek V4 FlashGoogle BigQuery, Snowflakeagainst: Databricks SQLGoogle BigQueryChangedno first choiceGoogle BigQueryagainst: Databricks SQL, SnowflakeSnowflakeagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
One alternative
Amazon RedshiftThree alternatives
Amazon Redshift, Databricks SQL, SnowflakeFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, SnowflakeFour alternatives
Amazon Redshift, ClickHouse Cloud, DuckDB, MotherDuckThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryLlama 4 Maverickno first choiceno first choiceHeldno first choiceno first choiceno first choiceagainst: Amazon Redshift, Google BigQuery
Qwen 3.7 FlashSnowflakeGoogle BigQueryChangedno first choiceAmazon Redshift, Google BigQueryagainst: Snowflakeno first choiceagainst: Amazon Redshift, Google BigQuery, Oracle RAC, Snowflake, Teradata Vantage
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, Microsoft Fabric Data Warehouse, SnowflakeKimi K2Google BigQueryGoogle BigQuery, SnowflakeChangedGoogle BigQuery, SnowflakeGoogle BigQueryagainst: SnowflakeGoogle BigQuery, Snowflakeagainst: Databricks SQLagainst: Amazon Redshift, Google BigQuery, IBM Db2 Warehouse, Oracle Autonomous Data Warehouse, Snowflake
Two alternatives
Amazon Redshift, SnowflakeTwo alternatives
ClickHouse Cloud, MotherDuckFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Microsoft Fabric Data WarehouseOne alternative
Amazon RedshiftOne alternative
Amazon RedshiftGLM 4.7 FlashXSnowflakeGoogle BigQueryChangedno first choiceGoogle BigQueryagainst: ClickHouse Cloud, DuckDBno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, ClickHouse Cloud, Google BigQuery, Google Document AI Warehouse, MotherDuck, Oracle Data Integration, Tinybird
Two alternatives
Amazon Redshift, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, SnowflakeTwo alternatives
Amazon Redshift, MotherDuckMiniMax M2.5SnowflakeSnowflakeHeldno first choiceGoogle BigQueryno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, Google BigQueryFive alternatives
Amazon Redshift, ClickHouse Cloud, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFour alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, SnowflakeOne alternative
Amazon RedshiftGPT-6 LunaSnowflakeSnowflakeHeldno first choiceGoogle BigQueryno first choiceagainst: Amazon Redshift, Azure Synapse dedicated SQL pool, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, SnowflakeMuse Glimmer 30BSnowflakeGoogle BigQuery, SnowflakeChangedGoogle BigQuery, SnowflakeGoogle BigQueryagainst: SnowflakeGoogle BigQuery, Snowflakeagainst: Amazon Redshift, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Azure SQL Database, Google BigQueryTwo alternatives
Amazon Redshift, ClickHouse CloudFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Microsoft Fabric Data WarehouseOne alternative
Amazon RedshiftSix alternatives
Amazon Redshift, Azure Synapse Analytics, ClickHouse Cloud, Databricks SQL, Microsoft Fabric Data Warehouse, MotherDuckBold 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. Full answer text is in the free responses file. Download the record
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 | 2026-10-01 12:02 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:12 | yes | 4 | 8 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:37 | yes | 8 | 22 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 12:47 | yes | 20 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 13:23 | yes | 23 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:58 | yes | 17 | 7 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:06 | yes | 23 | 31 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:57 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:31 | no | 0 | 32 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:05 | yes | 10 | 15 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:44 | yes | 13 | 31 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:59 | yes | 10 | 25 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:38 | yes | 5 | 14 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:32 | yes | 13 | 22 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:52 | yes | 18 | 10 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:52 | yes | 5 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:42 | yes | 9 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 09:07 | yes | 29 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:32 | yes | 15 | 5 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:02 | yes | 5 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:59 | yes | 22 | 31 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:19 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:08 | yes | 9 | 29 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:10 | yes | 20 | 42 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:25 | yes | 20 | 77 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:49 | yes | 10 | 29 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:39 | yes | 4 | 13 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:57 | yes | 14 | 22 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:41 | yes | 10 | 7 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:41 | yes | 5 | 6 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:34 | yes | 7 | 21 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 11:09 | yes | 20 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:43 | yes | 14 | 8 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:27 | yes | 9 | 6 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:11 | yes | 23 | 44 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:14 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:24 | yes | 5 | 33 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:11 | yes | 10 | 20 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:25 | no | 0 | 133 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:01 | yes | 8 | 15 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:58 | yes | 9 | 15 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:50 | yes | 14 | 35 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:47 | yes | 9 | 7 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:52 | no | 0 | 3 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:37 | yes | 13 | 25 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 13:45 | yes | 19 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:26 | yes | 19 | 6 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:14 | yes | 7 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:08 | yes | 20 | 30 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:46 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:13 | yes | 10 | 35 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:55 | yes | 15 | 16 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:26 | yes | 19 | 34 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:06 | yes | 9 | 21 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:56 | yes | 4 | 13 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:33 | yes | 14 | 27 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:22 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:45 | no | 0 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:18 | no | 0 | 18 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 08:23 | yes | 27 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:56 | yes | 19 | 9 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:06 | no | 0 | 10 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:36 | yes | 24 | 54 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:47 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:36 | no | 0 | 31 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:35 | yes | 13 | 35 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:39 | yes | 9 | 14 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:27 | no | 0 | 9 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:14 | yes | 2 | 19 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:23 | yes | 15 | 25 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:51 | yes | 16 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:06 | no | 0 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:35 | yes | 13 | 28 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 09:34 | yes | 18 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 13:44 | yes | 22 | 8 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:46 | yes | 5 | 8 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:30 | yes | 22 | 52 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:09 | yes | 9 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:10 | yes | 20 | 50 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:06 | yes | 24 | 22 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:53 | yes | 24 | 212 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:38 | yes | 17 | 31 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:47 | yes | 5 | 36 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:55 | yes | 12 | 26 s |
Noise floor in this category
Flips between the edition run and its calibration repeat. Six prompts per model is a small sample; the index-wide floor is the number to trust.
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Claude Haiku 4.5
2 of 3 flipped
GPT-5.4 mini
1 of 4 flipped
Gemini 3.5 Flash
2 of 4 flipped
Perplexity Sonar
2 of 4 flipped
Grok 4.1 Fast
2 of 4 flipped
Mistral Small
0 of 3 flipped
DeepSeek V4 Flash
4 of 6 flipped
Llama 4 Maverick
0 of 0 flipped
Qwen 3.7 Flash
4 of 4 flipped
Kimi K2
4 of 5 flipped
GLM 4.7 FlashX
5 of 5 flipped
MiniMax M2.5
0 of 3 flipped
GPT-6 Luna
0 of 3 flipped
Muse Glimmer 30B
3 of 5 flipped
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
Azure Synapse read as Azure Synapse Analytics
Azure Synapse (Microsoft) read as Azure Synapse Analytics
Databricks read as Databricks SQL
Databricks (Databricks SQL) read as Databricks SQL
Databricks SQL / Lakehouse read as Databricks SQL
Microsoft Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric Warehouse read as Microsoft Fabric Data Warehouse
Teradata read as Teradata Vantage
Unresolved, counted raw
Apache Iceberg
Azure Synapse dedicated SQL pool
Google Document AI Warehouse
Oracle RAC
Synapse Analytics (Azure)
Discontinued, still offered
No shut-down product was recommended here.