Interview scheduling for enterprise buyers
Asked as “interview scheduling software”, and as “recruiting coordination tool”, on behalf of an enterprise B2B company. 55 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
55%
Clear leader
55GoodTime09Calendly07Greenhouse29others
55% of first choices, clear leader.
Since September 2026▼−5Since September 2026: 56% → 51%, −5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.GoodTime held the lead, −5 points on 56%, 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
Calendly41%Clear leader▼−23Since September 2026: 62% → 38%, −23 points. Past the 13-point floor: movement. Read over the models both editions asked.Standing →Mid-marketCalendly20%Contested▲+1Since September 2026: 21% → 21%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
GoodTime55%Clear leader▼−5Since September 2026: 56% → 51%, −5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.This page
Calendly41%Clear leader▼−23Since September 2026: 62% → 38%, −23 points. Past the 13-point floor: movement. Read over the models both editions asked.Standing →Mid-marketCalendly20%Contested▲+1Since September 2026: 21% → 21%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseGoodTime55%Clear leader▼−5Since September 2026: 56% → 51%, −5 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
01GoodTime55%3%63endorsed leader▼−5Since September 2026: 56% → 51%, −5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.56% → 51%
GoodTime55%3%63endorsed leader▼−5Since September 2026: 56% → 51%, −5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.56% → 51%02Calendly9%59%51criticized challenger▲+8Since September 2026: 0% → 8%, +8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 8%
Calendly9%59%51criticized challenger▲+8Since September 2026: 0% → 8%, +8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 8%03
Greenhouse7%23%31accepted challenger▲+1Since September 2026: 7% → 8%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.7% → 8%
Greenhouse7%23%31accepted challenger▲+1Since September 2026: 7% → 8%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.7% → 8%04
Workday Recruiting5%0%11accepted challenger▼−1Since September 2026: 7% → 6%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.7% → 6%
Workday Recruiting5%0%11accepted challenger▼−1Since September 2026: 7% → 6%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.7% → 6%05
ModernLoop4%3%38accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 4%
ModernLoop4%3%38accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 4%06
candidate.fyi4%0%20accepted challenger▼−17Since September 2026: 21% → 4%, −17 points. Past the 13-point floor: movement. Read over the models both editions asked.21% → 4%
candidate.fyi4%0%20accepted challenger▼−17Since September 2026: 21% → 4%, −17 points. Past the 13-point floor: movement. Read over the models both editions asked.21% → 4%07
Cal.com2%33%15criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%
Cal.com2%33%15criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%08
HireVue2%33%18criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%
HireVue2%33%18criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%09Prelude2%29%17criticized 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
13
Lever0%38%16criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Lever0%38%16criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%12
VidCruiter0%7%15accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
VidCruiter0%7%15accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%10
Paradox0%6%32accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Paradox0%6%32accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%11
Ashby0%0%14accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Ashby0%0%14accepted 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 twenty-eight head-to-head pages: the top eight products, each against each
Calendly vs GreenhouseCalendly vs Cal.comCalendly vs KoalendarCalendly vs AshbyGoodTime vs LeverGoodTime vs ModernLoopGoodTime vs GreenhouseGoodTime vs Cal.comGoodTime vs KoalendarGoodTime vs AshbyLever vs ModernLoopLever vs GreenhouseLever vs Cal.comLever vs KoalendarLever vs AshbyModernLoop vs GreenhouseModernLoop vs Cal.comModernLoop vs KoalendarModernLoop vs AshbyGreenhouse vs Cal.comGreenhouse vs KoalendarGreenhouse vs AshbyCal.com vs KoalendarCal.com vs AshbyKoalendar vs Ashby
One product takes 55% of first choices here, so the chart would put twelve 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. Five products carry a negative rate above 25% in this category.
What they warned about
Four of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Grok 4.1 Fast, Mistral Small, DeepSeek V4 Flash, Llama 4 Maverick, Qwen 3.7 Flash, GLM 4.7 FlashX 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.
Calendly59%
30 of 51 labels negative · 13 of 14 models · 9 hard negative
“The primary categories of interview scheduling tools that large enterprises should **avoid or approach with heavy caution**... General-Purpose "Link-Sharing" Schedulers **Examples:** *Calendly...” Gemini 3.5 Flash, negative prompt
Microsoft Bookings67%
6 of 9 labels negative · 6 of 14 models · 3 hard negative
“avoid or be very cautious with: Consumer-grade link schedulers such as Calendly, Cal.com, Doodle, and Microsoft Bookings” Muse Glimmer 30B, negative prompt
Google Calendar100%
5 of 5 labels negative · 5 of 14 models · 3 hard negative
“General Consumer Booking Tools (e.g., Calendly, Google Calendar) ... dangerous choices for enterprise-scale recruiting” Qwen 3.7 Flash, negative prompt
HireVue33%
6 of 18 labels negative · 5 of 14 models · 1 hard negative
“High minimums (~$35,000/year) with pricing that escalates significantly” 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
78 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. 1107 links across 208 sites, every framing counted. Ranked by the number of answers carrying the site or page. 4 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 · Cal.com48 answers · 61 citations · 12 models
vendor site · GoodTime45 answers · 77 citations · 14 models
vendor site · Lever41 answers · 51 citations · 12 models
vendor site · Sapia.ai33 answers · 35 citations · 9 models
vendor site · Calendly26 answers · 40 citations · 10 models
vendor site · Intervue26 answers · 26 citations · 11 models
24 answers · 25 citations · 9 models
vendor site · Pin22 answers · 25 citations · 12 models
vendor site · Metaview21 answers · 23 citations · 10 models
20 answers · 43 citations · 10 models
vendor site · Agiled18 answers · 20 citations · 10 models
18 answers · 18 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.
42 answers · 10 models
34 answers · 11 models
32 answers · 10 models
32 answers · 9 models
25 answers · 11 models
20 answers · 9 models
19 answers · 9 models
18 answers · 10 models
18 answers · 8 models
17 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 interview scheduling software”, “interview scheduling software”, “interview scheduling 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 |
|---|---|---|---|---|---|---|---|---|
| GoodTime goodtime.io | 55% | 149 | 135,000 | 614 | 2,435 | $1,627 | 7 | 4 |
| Calendly calendly.com | 9% | 240 | 368,000 | 2,824 | 292,858 | $34 | 5 | |
| Greenhouse greenhouse.com | 7% | 419 | 301,000 | 52,273 | 62,551 | $5,545 | 74 | |
| Workday parent site Workday Recruiting 5% | 5% | 167 | 1,220,000 | 23,848 | ||||
| ModernLoop modernloop.com | 4% | 87 | 880 | 7 | 410 | |||
| candidate.fyi candidate.fyi | 4% | 35 | 210 | 0 | 494 | 10 | 1 | |
| Microsoft Bookings microsoft.com | 4% | 43 | 27,100 | 1,496 | 145,358,109 | $12,455 | 103 | |
| iCIMS icims.com iCIMS Talent Cloud 2% | 2% | 51 | 27,100 | 667 | 1,165,712 company | $5,674 | 26 | |
| SmartRecruiters smartrecruiters.com | 2% | 151 | 9,900 | 194 | 272,094 | 0 | ||
| Cal.com cal.com | 2% | 82 | 2,900 | 100 | 439,943 | 3 |
Google's top ten for the three searches hold 13 sites; 3 of them are among the sites the models cited here (candidate.fyi, goodtime.io, peoplemanagingpeople.com). The first result for “best interview scheduling software” is candidate.fyi.
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 interview scheduling software for an enterprise B2B company?”Paraphrase“Which recruiting coordination tool would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade interview scheduling tools and how do they differ?”Budget-constrained“What is the best interview scheduling software 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 an interview scheduling software. What should we look at?”Negative“Which interview scheduling tools should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5GoodTimeno first choiceChangedcandidate.fyiagainst: Calendly, HireVue, Spark HireGoodTimeno first choiceagainst: Acuity Scheduling, Cal.com, Calendly, Doodle, HireVue, Microsoft Bookings, Spark Hire, Willo
Two alternatives
HireVue, candidate.fyiFour alternatives
Ashby, GoodTime, ModernLoop, ParadoxTwo alternatives
Calendly, candidate.fyiGPT-5.4 miniRooster, candidate.fyiagainst: CalendlyGreenhouse, Workday RecruitingChangedno first choiceGoodTimeagainst: Calendlyno first choicenothing named
One alternative
PinpointTwo alternatives
Ashby, LeverSix alternatives
Ashby, GoodTime, Greenhouse, Paradox for Workday Recruiting, SmartRecruiters, Workday RecruitingTwo alternatives
Ashby, PreludeGemini 3.5 FlashGoodTime, ModernLoopagainst: Calendlycandidate.fyiChangedcandidate.fyiagainst: Calendly, Google CalendarGoodTimeagainst: CalendlyGoodTime, ModernLoop, Preludeagainst: Calendlyagainst: Acuity Scheduling, Calendly, Doodle, Greenhouse, Lever, Picktime, SavvyCal, Setmore, YouCanBookMe
Five alternatives
Ashby, Cal.com, Chili Piper, Paradox, candidate.fyiThree alternatives
GoodTime, ModernLoop, ParadoxFive alternatives
GoodTime, HireVue, ModernLoop, Paradox, VidCruiterThree alternatives
Cal.com, Paradox, candidate.fyiThree alternatives
Calendly, Cronofy, ParadoxPerplexity SonarGoodTimeGoodTimeHeldAvature, GoodTimeagainst: Calendly, Greenhouse, LeverGoodTimeagainst: CalendlyGoodTimenothing named
Two alternatives
Gem Scheduling, ParadoxTwo alternatives
SmartRecruiters, iCIMS Talent CloudFive alternatives
Ashby, ModernLoop, Paradox, Prelude, VidCruiterOne alternative
candidate.fyiSix alternatives
Cronofy, Doodle, HireVue, ModernLoop, Paradox, VidCruiterGrok 4.1 FastGoodTimeWorkday RecruitingChangedagainst: Greenhouse, Oracle TaleoGoodTimeagainst: Chili Piper, OnceHubMicrosoft Bookingsagainst: Chili Piper, GoodTime, HubSpot Meetings, Paradox, Prelude, SavvyCalGoodTimeagainst: Acuity Scheduling, Calendly, Google Appointment Schedule, Greenhouse, HireVue, HubSpot Meetings, Lever, Microsoft Bookings, SavvyCal
Five alternatives
Calendly, Chili Piper, ModernLoop, Paradox, PreludeTwo alternatives
SAP SuccessFactors, iCIMS Talent CloudTwo alternatives
Calendly, ModernLoopThree alternatives
Cal.com Organizations/Enterprise, Calendly, Google Workspace Appointment SchedulingOne alternative
candidate.fyiMistral SmallGoodTimeGreenhouseChangedGoodTimeGoodTimeno first choiceagainst: Calendly, X.aiagainst: Calendly, Google Calendar
Three alternatives
Calendly, HireVue, VidCruiterFive alternatives
Cal.com, Greenhouse, Intervue, Lever, VidCruiterTwo alternatives
ModernLoop, candidate.fyiThree alternatives
GoodTime, Paradox, ScheduleOnceDeepSeek V4 FlashGoodTimeagainst: Acuity Scheduling, Cal.com, Koalendar, PreludeGreenhouseChangedGoodTimeagainst: Calendly, LeverGoodTimeagainst: Cal.com, Calendly, ParadoxGoodTimeagainst: Calendly, Greenhouseagainst: Cal.com, Calendly, Google Calendar appointment slots, HireVue, Outlook booking, Spark Hire, myInterview
Two alternatives
Calendly Recruiting, ModernLoopFive alternatives
Ashby, SAP SuccessFactors Recruiting, SmartRecruiters, Workday Recruiting, iCIMS Talent CloudThree alternatives
Cal.com, ModernLoop, ParadoxOne alternative
HireVueTwo alternatives
Ashby, PreludeLlama 4 MaverickGoodTimeJobviteChangedCal.comCalendlyno first choicenothing named
Two alternatives
Greenhouse, SmartRecruitersEight alternatives
Calendly, FluentBooking, GoodTime, Greenhouse, Lever, ModernLoop, VidCruiter, candidate.fyiTwo alternatives
Paradox, VidCruiterQwen 3.7 FlashCalendly, GoodTimeiCIMS Talent CloudChangedGoodTimeagainst: Calendly, Microsoft BookingsCalendly, Microsoft Bookingsno first choiceagainst: Calendly, Google Calendar, HireVue, Microsoft Power Automate, VidCruiter
Three alternatives
Greenhouse, Lever, ParadoxTwo alternatives
SmartRecruiters, Workday RecruitingFour alternatives
Greenhouse, Lever, Paradox, YelloOne alternative
LimeKimi K2GoodTimeagainst: Greenhouse, LeverGoodTimeHeldagainst: SmartRecruitersGoodTime, ModernLoopagainst: CalendlyGoodTimeagainst: Calendly, HireVue, ModernLoopGoodTimeagainst: Calendlyagainst: Calendly, Doodle, Google Calendar, Greenhouse, Lever, Microsoft Bookings, When2meet
Three alternatives
Calendly, ModernLoop, ParadoxFour alternatives
Calendly, Greenhouse, ModernLoop, Workday RecruitingFour alternatives
Greenhouse, HireVue, Lever, SmartRecruitersOne alternative
AshbyTwo alternatives
ModernLoop, VidCruiterGLM 4.7 FlashXGoodTimeWorkday RecruitingChangedGoodTimeCal.comagainst: Calendlyno first choiceagainst: Calendly, Google Calendar, Prelude
Three alternatives
Calendly, Greenhouse, LeverFour alternatives
Greenhouse, HireVue, Paradox, iCIMS Talent CloudFour alternatives
Cal.com, Calendly, ModernLoop, ParadoxTwo alternatives
GoodTime, HireVueMiniMax M2.5GoodTime, HireVueGreenhouse, SmartRecruitersChangedGoodTimeCalendlyagainst: GoodTimeno first choiceagainst: Calendly
Two alternatives
Cal.com, Sapia.aiTwo alternatives
Workday Recruiting, iCIMS Talent CloudFour alternatives
Cal.com, HireVue, Paradox, VidCruiterOne alternative
Cal.comFour alternatives
Avature, ModernLoop, VidCruiter, candidate.fyiGPT-6 LunaGoodTimeGoodTimeHeldGoodTime, ModernLoopagainst: PreludeCalendlyno first choiceagainst: Calendly, Google Calendar appointment schedules, Microsoft Bookings, Prelude
Two alternatives
Greenhouse, ModernLoopOne alternative
CronofyThree alternatives
Cronofy, Workday Paradox, candidate.fyiOne alternative
GoodTimeMuse Glimmer 30BGoodTimeGoodTimeHeldGoodTimeGoodTimeagainst: Calendlyno first choiceagainst: Cal.com, Calendly, Doodle, Microsoft Bookings
Four alternatives
Greenhouse, SmartRecruiters, Workday Recruiting, iCIMS Talent CloudFive alternatives
Intervue, ModernLoop, Paradox, Prelude, candidate.fyiOne alternative
NoonBold 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 10:38 | yes | 9 | 7 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:39 | yes | 3 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:36 | yes | 18 | 30 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 08:01 | yes | 19 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:11 | yes | 23 | 8 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:13 | yes | 12 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:40 | yes | 21 | 29 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:34 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:52 | no | 0 | 27 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:55 | yes | 12 | 22 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:16 | yes | 22 | 26 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:56 | yes | 5 | 10 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:05 | yes | 4 | 15 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:41 | yes | 12 | 20 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:02 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:23 | yes | 5 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:41 | yes | 14 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 11:23 | yes | 19 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:37 | yes | 17 | 7 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:39 | yes | 5 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:20 | yes | 19 | 21 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:13 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:57 | yes | 10 | 31 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:56 | yes | 19 | 20 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:13 | yes | 13 | 21 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:46 | yes | 10 | 20 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:44 | yes | 2 | 5 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:51 | yes | 21 | 52 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:43 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:02 | yes | 8 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:23 | yes | 18 | 22 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 11:36 | yes | 20 | 6 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:41 | yes | 20 | 11 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:38 | yes | 11 | 9 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:50 | yes | 21 | 44 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:47 | yes | 5 | 4 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:43 | yes | 15 | 43 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:53 | yes | 24 | 29 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:30 | yes | 23 | 33 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:52 | yes | 23 | 33 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:07 | yes | 6 | 43 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:47 | yes | 19 | 56 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:24 | yes | 17 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:37 | yes | 5 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:44 | yes | 26 | 29 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 08:30 | yes | 19 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:59 | yes | 22 | 10 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:44 | yes | 5 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:15 | yes | 25 | 30 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:27 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:02 | no | 0 | 31 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:46 | yes | 22 | 20 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:07 | yes | 23 | 151 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:07 | yes | 20 | 52 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:39 | yes | 2 | 25 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:11 | yes | 18 | 37 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:11 | yes | 17 | 11 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:42 | yes | 5 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:27 | no | 0 | 16 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 09:19 | yes | 19 | 7 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:07 | yes | 19 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:53 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:45 | yes | 22 | 49 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:33 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:01 | no | 0 | 24 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:39 | yes | 12 | 19 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:06 | yes | 20 | 48 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:56 | yes | 5 | 18 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:05 | yes | 4 | 27 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:38 | yes | 13 | 23 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:51 | yes | 9 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:38 | yes | 3 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:18 | yes | 18 | 31 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 08:58 | yes | 18 | 3 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:39 | yes | 19 | 12 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:02 | yes | 13 | 8 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:12 | yes | 20 | 27 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:02 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:41 | yes | 14 | 44 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:37 | yes | 24 | 33 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:52 | yes | 22 | 34 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:50 | yes | 22 | 45 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:22 | yes | 4 | 23 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:57 | yes | 20 | 34 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
Acuity read as Acuity Scheduling
HubSpot read as HubSpot Meetings
Workday read as Workday Recruiting
iCIMS read as iCIMS Talent Cloud
Unresolved, counted raw
Cal.com Organizations/Enterprise
Calendly Recruiting
Clara
Clockwork
Google Calendar appointment schedules
Google Workspace Appointment Scheduling
Microsoft Power Automate
Ninjahire
Outlook booking
Paradox for Workday Recruiting
Workday Paradox
Discontinued, still offered
No shut-down product was recommended here.