Dashboards and data visualization for enterprise buyers
Asked as “business intelligence and dashboard tool”, and as “data visualization platform”, on behalf of an enterprise B2B company. 57 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
58%
Clear leader
58Microsoft Power BI26Tableau05Looker11others
58% of first choices, clear leader.
Since September 2026▼−11Since September 2026: 70% → 58%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.Microsoft Power BI held the lead, −11 points on 70%, 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 business
Microsoft Power BI37%Contested▲+1Since September 2026: 36% → 37%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketMicrosoft Power BI52%Clear leader▼−11Since September 2026: 62% → 51%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →EnterpriseMicrosoft Power BI58%Clear leader▼−11Since September 2026: 70% → 58%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.This page
Microsoft Power BI37%Contested▲+1Since September 2026: 36% → 37%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketMicrosoft Power BI52%Clear leader▼−11Since September 2026: 62% → 51%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →EnterpriseMicrosoft Power BI58%Clear leader▼−11Since September 2026: 70% → 58%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.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 September 2026
01Microsoft Power BI58%10%72endorsed leader▼−11Since September 2026: 70% → 58%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.70% → 58%
Microsoft Power BI58%10%72endorsed leader▼−11Since September 2026: 70% → 58%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.70% → 58%02
Tableau26%28%72criticized challenger▲+10Since September 2026: 17% → 27%, +10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.17% → 27%
Tableau26%28%72criticized challenger▲+10Since September 2026: 17% → 27%, +10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.17% → 27%03
Looker Lab in the set5%17%63accepted challenger▲+2Since September 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 4%
Looker Lab in the set5%17%63accepted challenger▲+2Since September 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 4%04
Sisense2%31%16criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Sisense2%31%16criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%Show the six products at 0%, ordered by negative rate
10
Metabase0%75%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Metabase0%75%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%09
Domo0%39%23criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Domo0%39%23criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%06
ThoughtSpot0%10%29accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
ThoughtSpot0%10%29accepted 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
Qlik Sense0%8%40accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
Qlik Sense0%8%40accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%07
Sigma0%7%15accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 0%
Sigma0%7%15accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 0%08
SAP Analytics Cloud0%0%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
SAP Analytics Cloud0%0%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 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.
Looker 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 three times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to head
All twenty-one head-to-head pages: the top seven products, each against each
Microsoft Power BI vs Zoho AnalyticsMicrosoft Power BI vs SigmaMicrosoft Power BI vs DomoLooker Studio vs TableauLooker Studio vs MetabaseLooker Studio vs Zoho AnalyticsLooker Studio vs SigmaLooker Studio vs DomoTableau vs MetabaseTableau vs Zoho AnalyticsTableau vs SigmaTableau vs DomoMetabase vs Zoho AnalyticsMetabase vs SigmaMetabase vs DomoZoho Analytics vs SigmaZoho Analytics vs DomoSigma vs Domo
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 →
01020304050607080910Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative70%
Key
01Microsoft Power BI58%
Microsoft Power BI58%02Tableau26%
Tableau26%03Looker5%
Looker5%04Sisense2%
Sisense2%05Qlik Sense0%
Qlik Sense0%06ThoughtSpot0%
ThoughtSpot0%07Sigma0%
Sigma0%08SAP Analytics Cloud0%
SAP Analytics Cloud0%09Domo0%
Domo0%10Metabase0%
Metabase0%What they warned about
Five of fourteen models held their first choice under the paraphrase. GPT-5.4 mini, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, DeepSeek V4 Flash, Qwen 3.7 Flash, GLM 4.7 FlashX, MiniMax M2.5 and GPT-6 Luna 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.
Tableau28%
20 of 72 labels negative · 12 of 14 models · 1 hard negative
“What to Avoid for Predictable Costs at Scale - **Tableau** ... cost explodes linearly with thousands of users.” DeepSeek V4 Flash, budget prompt
Looker17%
11 of 63 labels negative · 9 of 14 models
“Often cited as overly complex and expensive... It's only recommended if you already have a mature data infrastructure and team in place.” Mistral Small, negative prompt
Metabase75%
9 of 12 labels negative · 8 of 14 models · 5 hard negative
“Tools such as Looker Studio and Metabase Open Source fit that profile and are normally recommended for under-25-employee, no-data-team or small analytics use cases rather than enterprise-wide decisioning” Muse Glimmer 30B, negative prompt
Microsoft Power BI10%
7 of 72 labels negative · 7 of 14 models
“it has some drawbacks such as integration with other Microsoft services can increase overall spend, and minimum purchase requirements” Llama 4 Maverick, 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
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. 1066 links across 319 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 252 answers across every segment cited this index's own page for the category.
vendor site · Improvado24 answers · 29 citations · 11 models
vendor site · ThoughtSpot24 answers · 28 citations · 11 models
vendor site · Zoho23 answers · 29 citations · 10 models
vendor site · Qlik23 answers · 28 citations · 10 models
vendor site · Basedash18 answers · 29 citations · 10 models
vendor site · Holistics14 answers · 20 citations · 8 models
vendor site · Domo14 answers · 18 citations · 5 models
14 answers · 15 citations · 9 models
vendor site · LinkedIn14 answers · 15 citations · 8 models
vendor site · Microsoft13 answers · 24 citations · 5 models
vendor site · Querio13 answers · 16 citations · 6 models
13 answers · 16 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.
19 answers · 10 models
16 answers · 8 models
15 answers · 8 models
11 answers · 7 models
11 answers · 10 models
11 answers · 5 models
9 answers · 8 models
9 answers · 6 models
9 answers · 6 models
9 answers · 6 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 business intelligence and dashboard tool”, “business intelligence and dashboard tool”. 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 |
|---|---|---|---|---|---|---|---|---|
| Microsoft parent site Microsoft Power BI 58%, Microsoft Fabric 0% | 58% | 242 | 2,240,000 | 403,136 | ||||
| Tableau tableau.com | 26% | 215 | 135,000 | 15,635 | 1,201,809 | $23 | 85 | 3 |
| Google cloud.google.com Looker 5% | 5% | 155 | 18,100 | 2,051 | 7,405,347 | |||
| Sisense sisense.com | 2% | 45 | 2,400 | 140 | 29,511 | $243 | 15 | |
| Amazon QuickSight amazon.com | 2% | 6 | 2,900 | 176 | 1,681,997,879 | $106,125 | 115 | |
| Basedash basedash.com | 2% | 5 | ||||||
| Microsoft Power BI on Fabric capacity | 2% | |||||||
| Microsoft Power BI with Premium capacity | 2% | |||||||
| Power BI Premium Per Capacity | 2% | |||||||
| QlikView qlik.com Qlik Sense 0%, Qlik Cloud Analytics 0%, QlikView 0% | 0% | 73 | 3,600 | 379 | 705,831 | 55 | 1 |
Google's top ten for the two searches hold 16 sites; 3 of them are among the sites the models cited here (domo.com, qlik.com, thoughtspot.com). The first result for “best business intelligence and dashboard tool” 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 business intelligence and dashboard tool for an enterprise B2B company?”Paraphrase“Which data visualization platform would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade business intelligence tools and how do they differ?”Budget-constrained“What is the best business intelligence and dashboard tool 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 business intelligence and dashboard tool. What should we look at?”Negative“Which business intelligence tools should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Microsoft Power BI, TableauMicrosoft Power BI, TableauHeldMicrosoft Power BI, TableauMicrosoft Power BIno first choiceagainst: Domo, Metabase, Microsoft Power BI, Tableau
Two alternatives
Domo, LookerTwo alternatives
Looker, Qlik SenseTwo alternatives
Looker, Qlik SenseOne alternative
Amazon QuickSightGPT-5.4 miniMicrosoft Power BI, TableauTableauChangedMicrosoft Power BIMicrosoft Power BI on Fabric capacityagainst: Looker, Tableauno first choicenothing named
Two alternatives
Looker, Qlik SenseThree alternatives
Looker, Microsoft Power BI, Qlik SenseSeven alternatives
IBM Cognos Analytics, Looker, Oracle Analytics, Oracle BI, Qlik Sense, SAP Analytics Cloud, TableauThree alternatives
Looker, Microsoft Power BI, TableauGemini 3.5 FlashMicrosoft Power BIMicrosoft Power BIHeldMicrosoft Power BI, TableauMicrosoft Power BIagainst: TableauMicrosoft Power BIagainst: Tableauagainst: Evidence.dev, IBM Cognos Analytics, Lightdash, Looker Studio, Metabase, Oracle BI, SAP BusinessObjects, Tableau
Three alternatives
Looker, Sigma, TableauThree alternatives
Looker, Sigma, TableauFive alternatives
Databricks, Looker, Qlik Sense, Sigma, ThoughtSpotTwo alternatives
AWS QuickSight, Apache SupersetTwo alternatives
Looker, SigmaPerplexity SonarMicrosoft Power BITableauChangedno first choiceMicrosoft Power BIno first choiceagainst: Domo, Excel/Access-style "BI", Looker, Microsoft Power BI, Sisense, Tableau, ThoughtSpot
Four alternatives
Looker, Sisense, Tableau, ThoughtSpotFour alternatives
Domo, Microsoft Power BI, Qlik Sense, SisenseTwo alternatives
IBM Cognos Analytics, SAP Analytics CloudGrok 4.1 FastMicrosoft Power BITableauChangedMicrosoft Power BI, Tableauagainst: DomoMicrosoft Power BIagainst: Domo, Qlik Sense, Sisense, Tableau, ThoughtSpotno first choiceagainst: Apache Superset, Looker, Looker Studio, Metabase, Microsoft Power BI, Redash, Tableau, Zoho Analytics
Four alternatives
Looker, Qlik Sense, Tableau, ThoughtSpotTwo alternatives
Looker, Microsoft Power BIFour alternatives
Looker, Oracle Analytics, Qlik Sense, ThoughtSpotOne alternative
LookerMistral SmallSisense, Tableauno first choiceChangedno first choiceMicrosoft Power BIagainst: Looker, Tableauno first choiceagainst: IBM Cognos, Looker, MicroStrategy, Sisense
Three alternatives
IBM Cognos Analytics, Looker, Microsoft Power BIOne alternative
Microsoft FabricDeepSeek V4 FlashMicrosoft Power BI, TableauMicrosoft Power BIChangedagainst: Domo, Looker, Qlik SenseMicrosoft Power BIMicrosoft Power BIagainst: Looker Studio, Metabase, Power BI Pro only, Tableauno first choiceagainst: Domo, Looker, Metabase, Microsoft Power BI, Qlik Sense, Redash, Tableau, Zoho Analytics
Two alternatives
Looker, Qlik SenseOne alternative
TableauFive alternatives
Looker, Oracle Analytics, Qlik Sense, Tableau, ThoughtSpotThree alternatives
GoodData.AI, Qlik Cloud Analytics, SisenseLlama 4 Maverickno first choiceno first choiceHeldno first choiceBasedashTableauagainst: Looker, Microsoft Power BI, Tableau
Four alternatives
Microsoft Power BI, Qlik Sense, Querio, SisenseQwen 3.7 FlashMicrosoft Power BI, TableauMicrosoft Power BIChangedMicrosoft Power BI, TableauMicrosoft Power BIagainst: Domo, Sigma, Tableauno first choiceagainst: Apache Superset, Domo, Lightdash, Looker, Metabase, MicroStrategy, SAP BusinessObjects, Sisense, Tableau
Two alternatives
Looker, Qlik SenseTwo alternatives
Looker, TableauTwo alternatives
Domo, Qlik SenseOne alternative
Qlik Sense CloudKimi K2Microsoft Power BIMicrosoft Power BIHeldMicrosoft Power BI, TableauMicrosoft Power BIagainst: TableauMicrosoft Power BI, Tableauagainst: Apache Superset, Crystal Reports, Domo, IBM Cognos, Looker, Metabase, MicroStrategy, SAP BusinessObjects, SSRS, Sisense
Three alternatives
Looker, Tableau, ThoughtSpotTwo alternatives
Looker, TableauSix alternatives
IBM Cognos Analytics, Looker, MicroStrategy, Oracle Analytics, Qlik Sense, SAP BusinessObjectsOne alternative
ThoughtSpotOne alternative
LookerGLM 4.7 FlashXMicrosoft Power BIMicrosoft Power BI, TableauChangedMicrosoft Power BI, Tableauagainst: SAP BusinessObjectsPower BI Premium Per Capacityagainst: Tableauno first choiceagainst: Metabase, Microsoft Power BI, Tableau, Tableau Prep, ThoughtSpot, Zoho Analytics
Three alternatives
Domo, Looker, TableauTwo alternatives
Looker, Qlik SenseTwo alternatives
Looker, Qlik SenseFour alternatives
Looker, Metabase, Qlik Cloud Analytics, SupersetMiniMax M2.5Microsoft Power BILooker, Microsoft Power BIChangedagainst: TableauMicrosoft Power BI, Qlik Sense, TableauMicrosoft Power BI with Premium capacityagainst: Looker, TableauLooker, Microsoft Power BI, Tableauagainst: Microsoft Power BI, Tableau
Three alternatives
Domo, Looker, TableauThree alternatives
Looker, SAP Analytics Cloud, ThoughtSpotOne alternative
Amazon QuickSightGPT-6 LunaLookerMicrosoft Power BIChangedno first choiceMicrosoft Power BIno first choiceagainst: SAP BusinessObjects
Two alternatives
Microsoft Power BI, TableauTwo alternatives
Looker, TableauNine alternatives
Looker, Microsoft Power BI, Oracle Analytics, Qlik Cloud Analytics, Qlik Sense, SAP Analytics Cloud, Strategy One, Tableau, ThoughtSpotOne alternative
TableauFour alternatives
Looker, Microsoft Power BI, Sigma, TableauMuse Glimmer 30BMicrosoft Power BI, TableauMicrosoft Power BI, TableauHeldMicrosoft Power BI, TableauAmazon QuickSight, Microsoft Power BIagainst: Tableau Serverno first choiceagainst: Looker Studio, Metabase
Three alternatives
Looker, Looker Studio, Qlik SenseThree alternatives
Looker, Qlik Sense, SAP Analytics CloudFour alternatives
Looker, Qlik Sense, QlikView, SisenseBold 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 12:30 | yes | 9 | 9 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:15 | yes | 4 | 4 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:53 | yes | 14 | 23 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 10:15 | yes | 19 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:43 | yes | 20 | 13 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:48 | yes | 5 | 7 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:15 | yes | 24 | 25 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:58 | yes | 5 | 8 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:39 | yes | 5 | 22 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:04 | yes | 20 | 23 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:12 | yes | 15 | 21 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:27 | yes | 5 | 38 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:35 | yes | 3 | 10 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:23 | yes | 13 | 26 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:59 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:14 | yes | 3 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:14 | yes | 6 | 17 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 07:51 | yes | 20 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:01 | yes | 15 | 5 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:01 | no | 0 | 2 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:31 | yes | 24 | 23 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:12 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:44 | no | 0 | 32 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:13 | yes | 15 | 21 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:35 | no | 0 | 12 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:09 | yes | 10 | 20 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:38 | yes | 3 | 9 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:32 | yes | 15 | 25 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:49 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:33 | yes | 6 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 14:01 | yes | 15 | 37 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 13:58 | yes | 20 | 7 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:57 | yes | 25 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:01 | yes | 5 | 8 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:36 | yes | 23 | 46 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:05 | yes | 5 | 4 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:05 | yes | 5 | 21 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:19 | yes | 15 | 34 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:52 | yes | 25 | 169 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:49 | yes | 23 | 42 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:11 | yes | 8 | 28 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 13:48 | yes | 14 | 22 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:40 | yes | 18 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:21 | yes | 4 | 6 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:48 | yes | 14 | 32 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 11:54 | yes | 19 | 6 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:52 | yes | 25 | 10 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:23 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:16 | yes | 25 | 27 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:55 | yes | 5 | 1 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:54 | yes | 8 | 48 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:48 | yes | 25 | 22 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:18 | yes | 25 | 66 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:33 | yes | 22 | 109 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:40 | yes | 2 | 25 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:42 | yes | 20 | 31 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:16 | yes | 18 | 11 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:50 | yes | 3 | 10 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:45 | no | 0 | 15 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:38 | yes | 18 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 14:01 | yes | 19 | 11 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:51 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:04 | yes | 19 | 46 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:51 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:34 | yes | 5 | 31 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:24 | yes | 24 | 38 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:36 | yes | 15 | 30 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:41 | no | 0 | 14 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:40 | yes | 6 | 24 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:48 | yes | 15 | 23 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:12 | yes | 18 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:30 | yes | 5 | 8 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:31 | yes | 22 | 26 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 11:15 | yes | 19 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:32 | yes | 21 | 14 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:02 | yes | 5 | 6 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:06 | yes | 21 | 44 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:10 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:24 | yes | 19 | 38 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:40 | yes | 20 | 33 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:03 | yes | 23 | 80 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:43 | yes | 24 | 39 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:30 | yes | 2 | 21 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:19 | yes | 23 | 33 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
Oracle read as Oracle Analytics
Qlik read as Qlik Sense
Qlik (Qlik Sense) read as Qlik Sense
Qlik (QlikSense) read as Qlik Sense
Zoho read as Zoho Analytics
Unresolved, counted raw
Amazon QuickSight with Amazon Q
Apache Druid
Evidence.dev
Excel/Access-style "BI"
GoodData.AI (Enterprise)
Microsoft Power BI on Fabric capacity
Microsoft Power BI with Premium capacity (now Microsoft Fabric F64+)
Power BI Premium Per Capacity
Power BI Pro only
Pyramid Analytics
Qlik Sense Cloud
Strategy One
Tableau Prep
Tableau Server
Discontinued, still offered
No shut-down product was recommended here.