People analytics for enterprise buyers
Asked as “people analytics platform”, and as “HR analytics software”, on behalf of an enterprise B2B company. 47 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
57%
Clear leader
57Visier11ChartHop11Workday People Analytics21others
57% of first choices, clear leader.
Since September 2026▼−9Since September 2026: 65% → 56%, −9 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Visier held the lead, −9 points on 65%, inside the 13-point 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
BambooHR53%Clear leader▲+13Since September 2026: 41% → 54%, +13 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-market
Crunchr22%Contested▲+8Since September 2026: 15% → 23%, +8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
Visier57%Clear leader▼−9Since September 2026: 65% → 56%, −9 points. Inside the 13-point floor: within noise. Read over the models both editions asked.This page
BambooHR53%Clear leader▲+13Since September 2026: 41% → 54%, +13 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketCrunchr22%Contested▲+8Since September 2026: 15% → 23%, +8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseVisier57%Clear leader▼−9Since September 2026: 65% → 56%, −9 points. Inside the 13-point floor: within noise. 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
01Visier57%14%65endorsed leader▼−9Since September 2026: 65% → 56%, −9 points. Inside the 13-point floor: within noise. Read over the models both editions asked.65% → 56%
Visier57%14%65endorsed leader▼−9Since September 2026: 65% → 56%, −9 points. Inside the 13-point floor: within noise. Read over the models both editions asked.65% → 56%02
Workday People Analytics11%20%44accepted challenger▲+3Since September 2026: 9% → 12%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.9% → 12%
Workday People Analytics11%20%44accepted challenger▲+3Since September 2026: 9% → 12%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.9% → 12%03
ChartHop11%29%28criticized challenger▲+3Since September 2026: 9% → 12%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.9% → 12%
ChartHop11%29%28criticized challenger▲+3Since September 2026: 9% → 12%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.9% → 12%04Crunchr6%10%30accepted challenger▲+5Since September 2026: 0% → 5%, +5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 5%
Crunchr6%10%30accepted challenger▲+5Since September 2026: 0% → 5%, +5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 5%05
One Model2%8%36accepted challenger▼−2Since September 2026: 5% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.5% → 2%
One Model2%8%36accepted challenger▼−2Since September 2026: 5% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.5% → 2%06
SAP SuccessFactors2%21%14accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%
SAP SuccessFactors2%21%14accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%Show the four products at 0%, ordered by negative rate
10
Tableau0%40%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Tableau0%40%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%09
Microsoft Viva Insights0%36%11criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Microsoft Viva Insights0%36%11criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%07
Oracle Fusion HCM Analytics0%12%16accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Oracle Fusion HCM Analytics0%12%16accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%08
Culture Amp0%10%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Culture Amp0%10%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 13 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.
All fifteen head-to-head pages: the top six products, each against each
One product takes 57% of first choices here, so the chart would put nine 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
Eight of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, Llama 4 Maverick and MiniMax M2.5 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.
Workday People Analytics20%
9 of 44 labels negative · 8 of 14 models · 1 hard negative
“disclosed a 2025 data breach affecting employee PII at Chipotle” MiniMax M2.5, negative prompt
Visier14%
9 of 65 labels negative · 8 of 14 models
“vendors with recent material workforce cuts and opaque pricing such as Visier for renewal trust and support continuity” Muse Glimmer 30B, negative prompt
ChartHop29%
8 of 28 labels negative · 7 of 14 models · 2 hard negative
“Large enterprises should avoid smaller or mid-market-focused tools (e.g., ChartHop, Lattice, BambooHR)” Mistral Small, negative prompt
BambooHR57%
4 of 7 labels negative · 4 of 14 models · 3 hard negative
“Basic HR reporting; no advanced predictive attrition, workforce modeling, or AI insights. Suited for SMBs, not complex enterprise data.” Grok 4.1 Fast, 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. 1126 links across 280 sites, every framing counted. Ranked by the number of answers carrying the site or page. 35 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 · Workhuman41 answers · 43 citations · 12 models
27 answers · 27 citations · 12 models
vendor site · Visier24 answers · 45 citations · 10 models
vendor site · G224 answers · 24 citations · 11 models
vendor site · HiBob23 answers · 31 citations · 10 models
vendor site · Ordio22 answers · 22 citations · 10 models
21 answers · 25 citations · 9 models
vendor site · Eletive21 answers · 23 citations · 9 models
vendor site · ThoughtSpot21 answers · 21 citations · 9 models
20 answers · 21 citations · 10 models
vendor site · Zendikt20 answers · 20 citations · 8 models
vendor site · ThriveSparrow19 answers · 19 citations · 9 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.
39 answers · 12 models
27 answers · 12 models
24 answers · 11 models
22 answers · 10 models
21 answers · 9 models
21 answers · 9 models
21 answers · 9 models
20 answers · 10 models
20 answers · 8 models
19 answers · 9 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 people analytics platform”, “people analytics platform”, “people analytics platforms”. 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 | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|
| Visier visier.com | 57% | 259 | 2,400 | 72 | 40,267 | 16 | |
| Workday parent site Workday People Analytics 11%, Workday HCM 2% | 13% | 216 | 1,220,000 | 23,848 | |||
| ChartHop charthop.com | 11% | 365 | 2,900 | 16 | 6,238 | 0 | |
| Crunchr crunchr.com | 6% | 104 | 390 | 3 | 1,411 | 1 | 7 |
| One Model onemodel.co | 2% | 80 | 880 | 1,191 | 2,190 | 18 | 2 |
| SAP parent site SAP SuccessFactors 2%, SAP SuccessFactors Workforce Analytics 0%, SAP SuccessFactors People Analytics 0%, SAP People Intelligence 0% | 2% | 477 | 135,000 | 74,309 | |||
| Ordio ordio.com | 2% | 19 | 70 | 1 | 16,723 | ||
| Looker Studio | 2% | 40,500 | 452 | ||||
| PeopleInsight hireroad.com | 2% | 8 | |||||
| Microsoft Power BI | 2% | 14,800 | 515 |
Google's top ten for the three searches hold 14 sites; 2 of them are among the sites the models cited here (hr.university, peoplemanagingpeople.com). The first result for “best people analytics platform” is peoplemanagingpeople.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 people analytics platform for an enterprise B2B company?”Paraphrase“Which HR analytics software would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade people analytics platforms and how do they differ?”Budget-constrained“What is the best people analytics platform 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 people analytics platform. What should we look at?”Negative“Which people analytics platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5no first choiceVisierChangedVisierCrunchrno first choiceagainst: ChartHop, Microsoft Viva Glint, Workday People Analytics
Three alternatives
Oracle Fusion HCM Analytics, SAP SuccessFactors, Workday People AnalyticsThree alternatives
ChartHop, One Model, Workday People AnalyticsTwo alternatives
ChartHop, VisierGPT-5.4 miniVisierVisierHeldVisierVisieragainst: Workday People Analytics, Workday Prism Analyticsno first choicenothing named
One alternative
Workday People AnalyticsThree alternatives
Oracle Fusion HCM Analytics, SAP SuccessFactors People Analytics, Workday HCMSix alternatives
Microsoft Viva Glint, Microsoft Viva Insights, Oracle Fusion HCM Analytics, Orgvue, SAP People Intelligence, Workday People AnalyticsOne alternative
SAP People IntelligenceGemini 3.5 FlashVisierVisierHeldagainst: SAP SuccessFactors People Analytics, Workday People AnalyticsVisierVisierno first choiceagainst: ChartHop, Domo, HiBob Analytics, Hippo Metrics, Knoetic, Microsoft Power BI, Orgnostic, Sisense, Tableau, Workday People Analytics, Workday Prism Analytics
Three alternatives
ChartHop, One Model, Workday Prism AnalyticsThree alternatives
ADP DataCloud, Crunchr, One ModelSix alternatives
ADP DataCloud, Crunchr, Culture Amp, Dayforce People Analytics, One Model, Workday People AnalyticsTwo alternatives
Crunchr, One ModelPerplexity SonarVisierSAP SuccessFactors, Workday People AnalyticsChangedVisierChartHopno first choiceagainst: BambooHR, Culture Amp, Lattice, Leapsome, Oracle Fusion HCM Analytics, SAP SuccessFactors, Tableau, Visier
Three alternatives
One Model, SAP SuccessFactors People Analytics, Workday People AnalyticsSix alternatives
ADP Workforce Now, Agentnoon, Culture Amp, Orgvue, PeopleStrong, Workhuman iQFour alternatives
Crunchr, One Model, SAP SuccessFactors, Workday People AnalyticsFour alternatives
One Model, Orgnostic, Orgvue, VisierGrok 4.1 FastVisierWorkday HCMChangedVisierWorkday People Analyticsagainst: ChartHop, CrunchrCrunchr, Visieragainst: BambooHR, ChartHop, Crunchr, Eletive, HiBob, Lattice, Leapsome, Microsoft Viva Insights, Rippling, ThriveSparrow
Four alternatives
Dayforce, Eletive, Workday People Analytics, Workhuman iQFour alternatives
Dayforce, Oracle Fusion Cloud HCM, SAP SuccessFactors, VisierFive alternatives
Crunchr, One Model, Oracle Fusion HCM Analytics, SAP SuccessFactors Workforce Analytics, Workday People AnalyticsOne alternative
VisierTwo alternatives
ThoughtSpot, Workday Prism AnalyticsMistral SmallOne Model, VisierWorkday People AnalyticsChangedVisierChartHop, Visier, Workday People Analyticsno first choiceagainst: BambooHR, ChartHop, Lattice
Three alternatives
Culture Amp, Microsoft Viva Insights, RipplingTwo alternatives
ADP Workforce Now with DataCloud, AgentnoonSeven alternatives
ChartHop, Crunchr, Culture Amp, Eightfold AI, Orgvue, Workday People Analytics, WorklyticsDeepSeek V4 FlashVisierVisierHeldOne Model, VisierChartHopagainst: One ModelVisieragainst: Microsoft Viva Insightsagainst: BambooHR, Leapsome, One Model, Oracle Fusion HCM Analytics, SAP SuccessFactors' People Insights, ThriveSparrow, Visier, Workday People Analytics
Three alternatives
Crunchr, One Model, Workday People AnalyticsFour alternatives
One Model, Oracle Fusion Cloud HCM, SAP SuccessFactors Workforce Analytics, Workday People AnalyticsSix alternatives
ChartHop, Crunchr, Oracle Fusion HCM Analytics, Orgvue, SAP SuccessFactors Workforce Analytics, Workday People AnalyticsTwo alternatives
Crunchr, VisierThree alternatives
Crunchr, One Model, OrgvueLlama 4 MaverickOrdiono first choiceChangedVisierno first choiceno first choiceagainst: One Model, Visier, Workday People Analytics
Three alternatives
Agentnoon, Eletive, HRBenchTwo alternatives
Agentnoon, Workhuman iQQwen 3.7 FlashVisierVisierHeldVisierVisieragainst: ChartHop, Crunchrno first choiceagainst: Kronos, Microsoft Power BI, PeopleSoft, Qlik, Tableau
Two alternatives
ChartHop, OrdioThree alternatives
ChartHop, PeopleFluent, Workday People AnalyticsFive alternatives
ChartHop, Orgvue, Tableau, ThoughtSpot, Workday People AnalyticsTwo alternatives
One Model, Workday Prism AnalyticsKimi K2VisierVisierHeldOne Model, VisierChartHopagainst: 15Five, LatticeVisieragainst: Lattice Analyticsagainst: Microsoft Power BI, Microsoft Viva Insights, SAP SuccessFactors, Tableau, Visier
Two alternatives
Crunchr, One ModelTwo alternatives
SAP SuccessFactors Workforce Analytics, Workday Prism AnalyticsFive alternatives
Crunchr, Oracle Fusion HCM Analytics, SAP SuccessFactors Workforce Analytics, UKG Pro People Analytics / Workforce Intelligence Hub, Workday People AnalyticsTwo alternatives
Crunchr, VisierThree alternatives
ChartHop, Crunchr, One ModelGLM 4.7 FlashXVisierVisierHeldVisierChartHopagainst: Visierno first choicenothing named
Four alternatives
ChartHop, Crunchr, One Model, Workday People AnalyticsFour alternatives
ADP Workforce Now, Culture Amp, HiBob, Workday People AnalyticsSix alternatives
ChartHop, Culture Amp, Lattice, One Model, SAP SuccessFactors Workforce Analytics, Workday People AnalyticsOne alternative
CrunchrMiniMax M2.5no first choiceWorkday People AnalyticsChangedVisierLooker Studio, Microsoft Power BIagainst: ChartHopno first choiceagainst: Crossover's Worksmart, TINYpulse, Visier, Workday People Analytics, Zeroed-In Technologies
Five alternatives
ADP DataCloud, Microsoft Viva Insights, Oracle Fusion HCM Analytics, SAP SuccessFactors People Analytics, VisierFour alternatives
ADP DataCloud, Microsoft Viva Insights, One Model, Workday People AnalyticsThree alternatives
Anaplan, Visier, Workday Adaptive PlanningGPT-6 LunaVisierVisierHeldOne Model, VisierPeopleInsightagainst: Visierno first choiceagainst: Teramind, Workday People Analytics
Two alternatives
One Model, Workday People AnalyticsFour alternatives
One Model, Oracle Fusion HCM Analytics, SAP SuccessFactors, Workday People AnalyticsFive alternatives
Crunchr, Oracle Fusion HCM Analytics, Orgvue, SAP People Intelligence, Workday People AnalyticsOne alternative
One ModelMuse Glimmer 30BVisierVisierHeldVisierCrunchragainst: SAP SuccessFactors, Visier, Workday People Analyticsno first choiceagainst: ChartHop, Microsoft Viva Insights, Visier
Two alternatives
SAP SuccessFactors Workforce Analytics, Workday People AnalyticsThree alternatives
Oracle Fusion HCM Analytics, SAP SuccessFactors Workforce Analytics, Workday People AnalyticsSeven alternatives
ChartHop, Crunchr, One Model, Oracle Fusion HCM Analytics, SAP SuccessFactors People Analytics, UKG Pro Workforce Analytics, Workday People Analytics / Prism AnalyticsOne alternative
One ModelBold 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 08:02 | no | 0 | 3 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:11 | yes | 4 | 7 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:44 | yes | 15 | 23 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 09:06 | yes | 22 | 6 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:45 | yes | 23 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:45 | yes | 11 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:56 | yes | 21 | 57 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:08 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:47 | yes | 5 | 29 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:41 | yes | 12 | 20 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:12 | yes | 23 | 220 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:44 | yes | 5 | 18 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:15 | yes | 3 | 19 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:37 | yes | 22 | 27 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:40 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:33 | yes | 6 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:26 | yes | 8 | 17 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 11:32 | yes | 19 | 4 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:48 | yes | 22 | 11 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:45 | yes | 5 | 3 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:56 | yes | 21 | 32 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:29 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:21 | no | 0 | 34 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:29 | yes | 18 | 18 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:26 | yes | 12 | 52 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:23 | no | 0 | 58 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:00 | yes | 3 | 12 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:49 | yes | 15 | 20 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:14 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:39 | yes | 12 | 17 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:01 | yes | 21 | 33 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 07:44 | yes | 18 | 5 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:53 | yes | 22 | 12 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:52 | yes | 10 | 11 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:02 | yes | 23 | 56 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:15 | yes | 5 | 1 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:30 | yes | 18 | 77 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:09 | yes | 25 | 35 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:33 | yes | 19 | 69 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:42 | yes | 14 | 29 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:38 | yes | 8 | 19 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:22 | yes | 20 | 41 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:36 | yes | 15 | 12 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:14 | yes | 5 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:40 | yes | 14 | 31 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 07:45 | yes | 20 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:15 | yes | 20 | 9 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:21 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 07:37 | yes | 24 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:32 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:44 | yes | 20 | 158 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:39 | yes | 25 | 32 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:10 | yes | 20 | 145 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:48 | yes | 17 | 64 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:58 | yes | 3 | 19 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:24 | yes | 20 | 53 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:47 | yes | 18 | 16 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:46 | yes | 0 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:20 | yes | 8 | 27 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:55 | yes | 17 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:40 | yes | 14 | 9 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:52 | no | 0 | 10 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:58 | yes | 22 | 63 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:56 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:08 | yes | 5 | 38 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:02 | yes | 25 | 33 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:47 | yes | 12 | 27 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:25 | no | 0 | 8 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:57 | yes | 5 | 20 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:12 | yes | 25 | 34 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:31 | yes | 25 | 12 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:25 | yes | 7 | 8 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:16 | yes | 17 | 34 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 09:54 | yes | 19 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:54 | yes | 24 | 9 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:10 | yes | 5 | 4 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:25 | yes | 25 | 56 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:11 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:56 | no | 0 | 34 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:46 | yes | 24 | 32 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:40 | yes | 18 | 118 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:45 | yes | 25 | 40 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:33 | yes | 3 | 28 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:13 | yes | 22 | 31 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Oracle read as Oracle Fusion HCM Analytics
Oracle HCM read as Oracle Fusion Cloud HCM
Oracle HCM Cloud read as Oracle Fusion Cloud HCM
Power BI read as Microsoft Power BI
Power BI Pro read as Microsoft Power BI
Qualtrics read as Qualtrics EmployeeXM
SuccessFactors (SAP) read as SAP SuccessFactors
Workday read as Workday People Analytics
Workday Analytics read as Workday People Analytics
Workday Prism read as Workday Prism Analytics
Workday analytics read as Workday People Analytics
Workhuman read as Workhuman iQ
Workhuman (formerly Globoforce) read as Workhuman iQ
Unresolved, counted raw
ADP Workforce Now with DataCloud
Built-In Analytics (Workday / Oracle)
Crossover's Worksmart
Dayforce People Analytics
Domo
HiBob Analytics
Hippo Metrics
Qlik Sense
SAP SuccessFactors' People Insights
Sisense
UKG Pro People Analytics / Workforce Intelligence Hub
Your HCM's native analytics (Workday, SuccessFactors, Oracle)
Zeroed-In Technologies
Discontinued, still offered
No shut-down product was recommended here.