HR AI Index
Index Talent acquisition Interview scheduling › Calendly vs Workable
Interview scheduling · September 2026 Edition

Calendly vs Workable

Zero of twelve models named Calendly first on the direct prompt; zero named Workable. Calendly was named by twelve of the twelve models and Workable by ten and Calendly carries 52 labels and Workable 12, so the shares are not directly comparable.

Calendly

criticized challenger

Named in two categories this edition.

Workable

accepted challenger

Named in nine categories this edition.

First-choice share21%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate40%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#8A position in a field of 11; printed, not drawn.
Labels5212A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Calendly reading right to left. Rank and label count are printed, not drawn.ModernLoop was named alongside these two in ten of the twelve direct answers. Calendly vs ModernLoop · Calendly vs Greenhouse · Calendly vs Koalendar

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the interview scheduling page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
CalendlyFirst choices, of twelve modelsWorkable
Direct005 against Calendly
Paraphrase121 against Calendly
Comparative302 against Calendly
Budget-constrained902 against Calendly · 1 against Workable
Scale-constrained103 against Calendly
Negative108 against Calendly
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Calendly and Workable stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Calendly Workable first choice named as an alternative argued againstblank: not namedEach cell is one answer, Calendly on the left and Workable on the right.

The direct prompt

The plain question, one answer per model, grouped by where Calendly and Workable stood in it.

Neither was the first choice, one was named

4 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Cronofy, Greenhouse alternatives: Calendly, Koalendar, ModernLoop
GPT-5.4 miniGoodTime alternatives: Ashby, Calendly
DeepSeek V4 FlashGreenhouse, ModernLoop alternatives: Ashby, Calendly, Lever
Qwen 3.7 FlashGreenhouse alternatives: Calendly, GoodTime, Lever, LimeLight, Lunacal

Neither was named

8 of 12 modelsThe answer made no first choice from these two in this category.
Gemini 3.5 FlashModernLoop alternatives: Ashby, candidate.fyi
Perplexity SonarModernLoop alternatives: GoodTime, Lever
Grok 4.1 FastGoodTime, Lever alternatives: Greenhouse, ModernLoop
Mistral SmallLever alternatives: Koalendar, ModernLoop
Llama 4 MaverickModernLoop alternatives: Greenhouse, Lever
Kimi K2Lever alternatives: GoodTime, Greenhouse, ModernLoop
GLM 4.7 FlashXModernLoop alternatives: GoodTime, Lever, candidate.fyi
MiniMax M2.5Cal.com, Lever alternatives: GoodTime, Greenhouse, ModernLoop

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Calendly leads by sixty points.
Calendly62%#1 of 11
Workable2%#– of 11
The full small business standing →
Mid-marketThe figures above
Calendly leads by seventeen points.
Calendly21%#1 of 11
Workable4%#8 of 11
The full mid-market standing →
Enterprise
Workable is not named for this buyer.
Calendly0%#9 of 9
Workablenot named
The full enterprise standing →

What the models said about Calendly

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.

“it's frequently cited as a tool recruiting teams outgrow quickly: Built for two-party scheduling, not complex panel interviews” Kimi K2 · negative prompt · hard negative
“basic scheduling links (like standard Calendly) or relying entirely on manual emails will severely bottleneck your growth... Breaks down completely once you try to schedule 3-person panel loops” Gemini 3.5 Flash · scale prompt · soft negative
“Why to be cautious: These platforms are fantastic for lightweight, 1-on-1 recruiter phone screens. However, they quickly fall apart if you try to use them for multi-stage or panel interviews.” Gemini 3.5 Flash · negative prompt · soft negative
“Calendly – Offers a free plan that includes basic scheduling, calendar sync, and reminders. It's user-friendly and widely used” Mistral Small · budget prompt · first choice
“Calendly is the most popular name in the category... Choose Calendly if you have a small team, diverse needs (sales + hiring)” Qwen 3.7 Flash · comparative prompt · first choice
“Calendly Enterprise: The gold standard for basic functionality. Highly customizable, but can be expensive per-seat.” Qwen 3.7 Flash · scale prompt · first choice

What the models said about Workable

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.

“Avoid ATS-style recruiting platforms like Breezy HR, Workable, or GoodTime if budget is tight” Perplexity Sonar · budget prompt · hard negative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.