Financial modeling and scenario planning
Asked as “financial modeling software”, and as “scenario planning tool for finance”, on behalf of a mid-market B2B company. 66 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
14%
Contested · Cube 12%
14Microsoft Excel12Cube12Vena62others
14% of first choices, contested.
Since September 2026↗new leaderNew leader since September 2026: Cube (12%) replaces Datarails (19% then, 11% now), 2 points clear, inside the 10-point floor.Cube leads at 12%, replacing Datarails, which led at 19% and stands at 11% now: 2 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 Sheets19%Contested↗new leaderNew leader since September 2026: Google Sheets (16%) replaces Clockwork (12% then, 2% now), 14 points clear, past the 10-point floor.Standing →Mid-market
Microsoft Excel14%Contested↗new leaderNew leader since September 2026: Cube (12%) replaces Datarails (19% then, 11% now), 2 points clear, inside the 10-point floor.This pageEnterprise
Anaplan57%Clear leader▼−1Since September 2026: 56% → 56%, −1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →
Google Sheets19%Contested↗new leaderNew leader since September 2026: Google Sheets (16%) replaces Clockwork (12% then, 2% now), 14 points clear, past the 10-point floor.Standing →Mid-marketMicrosoft Excel14%Contested↗new leaderNew leader since September 2026: Cube (12%) replaces Datarails (19% then, 11% now), 2 points clear, inside the 10-point floor.This pageEnterpriseAnaplan57%Clear leader▼−1Since September 2026: 56% → 56%, −1 point. Inside the 10-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
01Microsoft Excel14%24%17accepted challenger▲+2Since September 2026: 11% → 12%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 12%
Microsoft Excel14%24%17accepted challenger▲+2Since September 2026: 11% → 12%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 12%02
Cube12%0%32accepted challenger▲+2Since September 2026: 11% → 12%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 12%
Cube12%0%32accepted challenger▲+2Since September 2026: 11% → 12%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 12%03
Vena12%5%21accepted challenger▲+6Since September 2026: 6% → 12%, +6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 12%
Vena12%5%21accepted challenger▲+6Since September 2026: 6% → 12%, +6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 12%04
Datarails11%0%20accepted challenger▼−9Since September 2026: 19% → 11%, −9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.19% → 11%
Datarails11%0%20accepted challenger▼−9Since September 2026: 19% → 11%, −9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.19% → 11%05Google Sheets Lab in the set9%15%13accepted challenger▼−6Since September 2026: 13% → 7%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.13% → 7%
Google Sheets Lab in the set9%15%13accepted challenger▼−6Since September 2026: 13% → 7%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.13% → 7%06
Drivetrain6%0%11accepted challenger▲+3Since September 2026: 4% → 7%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 7%
Drivetrain6%0%11accepted challenger▲+3Since September 2026: 4% → 7%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 7%07
Prophix6%10%10accepted challenger▲+7Since September 2026: 0% → 7%, +7 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 7%
Prophix6%10%10accepted challenger▲+7Since September 2026: 0% → 7%, +7 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 7%08
Workday Adaptive Planning6%35%17criticized challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%
Workday Adaptive Planning6%35%17criticized challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%09
Planful3%11%19accepted challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 2%
Planful3%11%19accepted challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 2%10
Abacum3%7%15accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 4%
Abacum3%7%15accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 4%11
Jirav2%0%10accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 2%
Jirav2%0%10accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 2%12
Pigment2%8%12accepted challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 2%
Pigment2%8%12accepted challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 2%Show the two products at 0%, ordered by negative rate
14Anaplan0%75%24criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
Anaplan0%75%24criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%13
Mosaic0%17%12accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 0%
Mosaic0%17%12accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 0%The floor is 10 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 Sheets 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 six times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
All twenty-eight head-to-head pages: the top eight products, each against each
Microsoft Excel vs Google SheetsMicrosoft Excel vs DrivetrainMicrosoft Excel vs ProphixMicrosoft Excel vs Workday Adaptive PlanningCube vs VenaCube vs DatarailsCube vs Google SheetsCube vs DrivetrainCube vs ProphixCube vs Workday Adaptive PlanningVena vs DatarailsVena vs Google SheetsVena vs DrivetrainVena vs ProphixVena vs Workday Adaptive PlanningDatarails vs Google SheetsDatarails vs DrivetrainDatarails vs ProphixDatarails vs Workday Adaptive PlanningGoogle Sheets vs DrivetrainGoogle Sheets vs ProphixGoogle Sheets vs Workday Adaptive PlanningDrivetrain vs ProphixDrivetrain vs Workday Adaptive PlanningProphix vs Workday Adaptive Planning
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 →
0102030405060708091011121314Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Microsoft Excel14%
Microsoft Excel14%02Cube12%
Cube12%03Vena12%
Vena12%04Datarails11%
Datarails11%05Google Sheets9%
Google Sheets9%06Drivetrain6%
Drivetrain6%07Prophix6%
Prophix6%08Workday Adaptive Planning6%
Workday Adaptive Planning6%09Planful3%
Planful3%10Abacum3%
Abacum3%11Jirav2%
Jirav2%12Pigment2%
Pigment2%13Mosaic0%
Mosaic0%14Anaplan0%
Anaplan0%What they warned about
One of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, DeepSeek V4 Flash, Llama 4 Maverick, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5, GPT-6 Luna 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.
Anaplan75%
18 of 24 labels negative · 10 of 14 models · 3 hard negative
“Avoid for Mid-Market: Anaplan's licensing and implementation costs are significant” Claude Haiku 4.5, paraphrase prompt
Workday Adaptive Planning35%
6 of 17 labels negative · 5 of 14 models
“cannot afford enterprise FP&A software (like Workday Adaptive Planning or Anaplan, which cost tens of thousands of dollars annually)” Gemini 3.5 Flash, budget prompt
Microsoft Excel24%
4 of 17 labels negative · 3 of 14 models
“**Overly complex Excel hacks**: Circular references, OFFSET/INDIRECT functions, or hard-coded constants breed errors and slow performance.” Grok 4.1 Fast, negative prompt
Mosaic17%
2 of 12 labels negative · 2 of 14 models · 1 hard negative
“Avoid discontinued tools:** Causal, Pry, and Mosaic have been acquired and shut down” Kimi K2, budget 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
71 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. 947 links across 329 sites, every framing counted. Ranked by the number of answers carrying the site or page. 2 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 · Drivetrain38 answers · 59 citations · 12 models
vendor site · Abacum29 answers · 34 citations · 11 models
vendor site · Datarails24 answers · 26 citations · 12 models
vendor site · G221 answers · 24 citations · 10 models
20 answers · 20 citations · 11 models
vendor site · Guideflow19 answers · 22 citations · 9 models
vendor site · Cubesoftware17 answers · 20 citations · 11 models
14 answers · 16 citations · 7 models
vendor site · Hebbia14 answers · 14 citations · 9 models
vendor site · Worldmetrics12 answers · 22 citations · 7 models
12 answers · 13 citations · 8 models
vendor site · Centage11 answers · 15 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.
32 answers · 12 models
22 answers · 11 models
19 answers · 10 models
17 answers · 10 models
14 answers · 7 models
14 answers · 9 models
12 answers · 10 models
10 answers · 8 models
10 answers · 6 models
9 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 financial modeling software”, “financial modeling software”, “modeling tools”. 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 Excel microsoft.com | 14% | 137 | 135,000 | 4,387 | 145,358,109 | $12,455 | 103 | |
| Cube cubesoftware.com | 12% | 349 | 90,500 | 152,613 | 168,764 | 13 | 4 | |
| Vena venasolutions.com | 12% | 344 | 12,100 | 3,928 | 62,294 | $13,792 | 58 | |
| Datarails datarails.com | 11% | 303 | 6,600 | 134 | 18,964 | $16,697 | 107 | |
| Google Sheets google.com | 9% | 100 | 3,350,000 | 53,730 | 1,800,358,416 | $465,944 | 5 | |
| Drivetrain drivetrain.ai | 6% | 103 | 18,100 | 2,818 | 8,983 | $134 | 1 | 6 |
| Prophix prophix.com | 6% | 237 | 1,600 | 41 | 14,138 | $109 | 103 | 4 |
| Workday workday.com Workday Adaptive Planning 6% | 6% | 407 | 1,220,000 | 23,848 | 2,213,450 company | 80 | ||
| Planful planful.com | 3% | 341 | 3,600 | 685,726 | 58,997 | $137 | 120 | |
| Abacum abacum.ai | 3% | 73 | 1,300 | 18 | 79,014 | $26 | 16 | 2 |
Google's top ten for the three searches hold 21 sites; 5 of them are among the sites the models cited here (abacum.ai, cubesoftware.com, drivetrain.ai, fathomhq.com, hebbia.com). The first result for “best financial modeling software” is intl.finebi.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 financial modeling software for a mid-market B2B company?”Paraphrase“Which scenario planning tool for finance would you recommend to a mid-sized B2B company?”Comparative“What are the top modeling tools and how do they differ?”Budget-constrained“What is the best financial modeling software for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a financial modeling software. What should we look at?”Negative“Which modeling tools should I avoid or be cautious about?”
Claude Haiku 4.5DatarailsCubeChangedagainst: AnaplanER/StudioFathom, LivePlanno first choicenothing named
Four alternatives
Cube, Drivetrain, Planful, Prophix OneThree alternatives
Limelight, Mosaic, PigmentThree alternatives
Erwin Data Modeler, MySQL Workbench, pgModelerThree alternatives
Compass AI, Google Sheets, Microsoft ExcelGPT-5.4 miniDatarails, PlanfulVenaChangedagainst: Anaplanno first choiceMicrosoft Excelagainst: Abacum, Mosaic, Planful, Venano first choicenothing named
Two alternatives
Anaplan, VenaOne alternative
Workday Adaptive PlanningThree alternatives
Cube, Google Sheets, LibreOffice CalcGemini 3.5 FlashAleph, CubeDrivetrainChangedagainst: Anaplan, Workday Adaptive PlanningCube, Microsoft Excelagainst: AnaplanLivePlanagainst: Anaplan, Workday Adaptive PlanningCube, Venaagainst: Django ORM, FreeCAD, Google Sheets, Hibernate, Microsoft Excel, Prisma, SketchUp
Four alternatives
Abacum, Bob Finance, Pigment, VenaFour alternatives
Abacum, Cube, Pigment, VenaTwo alternatives
Jirav, MosaicFour alternatives
Budgeto, Excel or Google Sheets, Float, ParallelFour alternatives
Abacum, Mosaic, Planful, Workday Adaptive PlanningPerplexity SonarDatarails, LimelightCube, ProphixChangedno first choiceMicrosoft Excelno first choicenothing named
Two alternatives
Abacum, Workday Adaptive PlanningOne alternative
AnaplanSix alternatives
Cube, Datarails, Finmark, Google Sheets, Jirav, LiveFlowGrok 4.1 FastCube, Datarails, Drivetrain, JiravProphixChangedagainst: Planful, Workday Adaptive Planningno first choiceGoogle Sheets, Microsoft Excelno first choiceagainst: Anaplan, Microsoft Excel, Oracle Fusion Cloud EPMagainst: Google Sheets, Microsoft Excel, dbt
One alternative
AbacumTwo alternatives
Cube, VenaFive alternatives
Causal, Cube, Fathom, Finmark, LivePlanFive alternatives
Cube, Datarails, Jirav, Pigment, ProphixMistral SmallAbacumCube, VenaChangedno first choiceGoogle Sheets, Microsoft Excelno first choiceagainst: Oracle Hyperionnothing named
Two alternatives
Cube, DatarailsTwo alternatives
Drivetrain, PlanfulTwo alternatives
BILL, JiravDeepSeek V4 FlashCubeagainst: AnaplanCentage Planning MaestroChangedagainst: Anaplan, Pigmentno first choiceFinancial Modelling Prono first choiceagainst: Anaplannothing named
Four alternatives
Datarails, Jirav, Planful, VenaThree alternatives
Datarails, Planful, VenaFour alternatives
Compass AI, Excel or Google Sheets, Fathom, LivePlanFour alternatives
Pigment, Planful, Vena, Workday Adaptive PlanningLlama 4 Maverickno first choiceProphixChangedno first choiceFinancial Modelling Prono first choicenothing named
Qwen 3.7 FlashVena, Workday Adaptive Planningagainst: AnaplanVena, Workday Adaptive PlanningHeldagainst: Anaplanno first choiceMicrosoft Excelagainst: Anaplan, Workday Adaptive Planningno first choicenothing named
Two alternatives
Fathom, PlanGuruOne alternative
DatarailsFour alternatives
Finmark, Google Sheets, Jirav, LibreOffice CalcKimi K2Drivetrainagainst: Anaplan, Workday Adaptive PlanningProphix, VenaChangedagainst: Anaplanno first choiceGoogle Sheets, Microsoft Excelagainst: Causal, Mosaic, PryDatarails, Pigment, Vena, Workday Adaptive Planningagainst: Anaplan, OneStreamagainst: SketchUp
Two alternatives
Mosaic, PigmentOne alternative
MosaicFour alternatives
Financial Modelling Pro, Finmark, PlanGuru, UniflowGLM 4.7 FlashXDatarailsAbacumChangedno first choiceGoogle Sheets, Microsoft Excelagainst: Budgytno first choiceagainst: Anaplan, Oracle Fusion Cloud EPM, Prophix, SAP Analytics Cloud, Workday Adaptive Planningnothing named
Four alternatives
Abacum, Cube, Lucanet xP&A, MosaicThree alternatives
Centage Planning Maestro, Cube, PlanfulThree alternatives
Finmark, Jirav, PlanGuruMiniMax M2.5DrivetrainCentage Planning MaestroChangedagainst: Anaplanno first choiceUpmetricsno first choiceagainst: Oracle Hyperionnothing named
Four alternatives
Abacum, Cube, Datarails, PigmentFour alternatives
Cube, Datarails, Planful, VenaFour alternatives
Budgyt, FreshBooks, Google Sheets, Microsoft ExcelGPT-6 LunaWorkday Adaptive Planningagainst: Anaplan, Microsoft ExcelPlanfulChangedno first choiceGoogle Sheets, Microsoft Excelno first choicenothing named
Two alternatives
Cube, VenaTwo alternatives
Pigment, Workday Adaptive PlanningOne alternative
LibreOffice CalcMuse Glimmer 30BDatarailsCube, VenaChangedno first choiceGoogle Sheets, Microsoft Excelno first choicenothing named
Four alternatives
Cube, Drivetrain, Mosaic, PlanfulThree alternatives
Centage Planning Maestro, Planful, ProphixTwo alternatives
Finmark, VizuleBold 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 09:19 | yes | 9 | 7 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:36 | yes | 3 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:43 | yes | 17 | 28 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 09:06 | yes | 20 | 2 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:21 | yes | 20 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:44 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:54 | yes | 16 | 37 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:00 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:09 | no | 0 | 29 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:25 | yes | 14 | 21 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:36 | yes | 9 | 15 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:43 | yes | 7 | 28 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:11 | yes | 4 | 19 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:59 | yes | 12 | 15 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:57 | yes | 9 | 8 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:11 | no | 0 | 3 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:47 | yes | 16 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 11:14 | yes | 20 | 4 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:32 | yes | 19 | 7 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:48 | yes | 5 | 3 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:19 | yes | 24 | 32 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:33 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:23 | yes | 10 | 43 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:14 | yes | 15 | 31 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:59 | yes | 21 | 25 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:02 | yes | 14 | 27 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:08 | yes | 4 | 14 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:01 | yes | 13 | 25 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:47 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:19 | no | 0 | 6 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:52 | yes | 19 | 24 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 09:25 | yes | 18 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:56 | yes | 25 | 11 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:11 | yes | 10 | 8 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:15 | yes | 20 | 48 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:45 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:16 | no | 0 | 23 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:31 | yes | 20 | 28 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:06 | yes | 24 | 114 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:57 | yes | 18 | 68 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:17 | no | 0 | 4 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:44 | yes | 15 | 25 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:47 | yes | 9 | 7 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:31 | no | 0 | 3 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:02 | yes | 17 | 19 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 08:58 | yes | 19 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:46 | yes | 24 | 6 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:11 | yes | 5 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:34 | yes | 25 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:22 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:33 | yes | 5 | 19 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:24 | yes | 13 | 22 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:05 | yes | 24 | 201 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:04 | yes | 5 | 18 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:10 | yes | 3 | 12 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:44 | yes | 15 | 15 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:24 | no | 0 | 5 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:09 | no | 0 | 9 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:20 | no | 0 | 16 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:01 | yes | 20 | 7 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:47 | yes | 13 | 13 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:36 | no | 0 | 6 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:15 | yes | 24 | 50 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:13 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:56 | yes | 5 | 21 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:46 | yes | 10 | 36 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:16 | yes | 14 | 58 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:25 | yes | 5 | 20 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:18 | yes | 3 | 15 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:24 | yes | 13 | 21 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:26 | no | 0 | 2 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:37 | yes | 4 | 4 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:35 | yes | 19 | 26 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 08:06 | yes | 15 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:07 | yes | 25 | 8 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:47 | no | 0 | 1 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:30 | yes | 9 | 20 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:12 | yes | 5 | 1 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:11 | yes | 20 | 49 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:57 | yes | 25 | 23 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:31 | yes | 22 | 83 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:09 | yes | 9 | 36 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:38 | no | 0 | 4 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:47 | yes | 14 | 19 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
Adaptive Insights read as Workday Adaptive Planning
Adaptive Insights (Workday) read as Workday Adaptive Planning
Centage read as Centage Planning Maestro
Excel read as Microsoft Excel
Oracle Cloud EPM read as Oracle Fusion Cloud EPM
Oracle EPM read as Oracle Fusion Cloud EPM
Vena Solutions read as Vena
Workday Adaptive read as Workday Adaptive Planning
Unresolved, counted raw
Boldin
Decipad
Django ORM
Finta
Hackolade
Hibernate
Hunyuan3D
Maya
Meshy
Prisma
Rodin
Tripo
Vizule
Discontinued, still offered
No shut-down product was recommended here.