Calendly vs Lever
Zero of twelve models named Calendly first on the direct prompt; four named Lever. Calendly was named by twelve of the twelve models and Lever by eleven and Calendly carries 52 labels and Lever 28, so the shares are not directly comparable.
Named in two categories this edition.
Named in nine categories this edition.
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
CalendlyFirst choices, of twelve modelsLever
Across every category in the September 2026 Edition, Calendly and Lever were named in the same answer fifty times, of the 218 answers naming Calendly and the 255 naming Lever. In those answers Lever took the first choice five times and Calendly seventeen.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 Lever first choice named as an alternative argued againstblank: not namedEach cell is one answer, Calendly on the left and Lever on the right.The direct prompt
Lever first, Calendly not the choice
4 of 12 modelsCalendly was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 12 modelsThe answer made no first choice from these two in this category.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
Calendly0%#9 of 9Lever0%#8 of 9What 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 Lever
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“its native scheduling tool is frequently cited by users as having the "absolute worst UX."” Qwen 3.7 Flash · negative prompt · hard negative
“Less structured tools, pricier renewals ... they're overkill (and 2-5x costlier) for most mid-sized B2B ops” Grok 4.1 Fast · paraphrase prompt · soft negative
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.