GoodTime vs Greenhouse
Three of fourteen models named GoodTime first on the direct prompt; zero named Greenhouse. GoodTime was named by fourteen of the fourteen models and Greenhouse by thirteen and GoodTime carries 54 labels and Greenhouse 23, so the shares are not directly comparable.
Named in two categories this edition.
Named in fourteen categories this edition.
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; 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
GoodTimeFirst choices, of fourteen modelsGreenhouse
Across every category in the November 2026 Edition, GoodTime and Greenhouse were named in the same answer sixty-six times, of the 166 answers naming GoodTime and the 456 naming Greenhouse. In those answers Greenhouse took the first choice four times and GoodTime twenty-eight.
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 4.20 | | | | | | |
| Mistral Small | | | ||||
| DeepSeek V4 Flash | | | | | ||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | | ||
| Kimi K2 | | | | | | |
| GLM 4.7 FlashX | | | | |||
| MiniMax M2.5 | | | | | ||
| GPT-6 Luna | | | | | ||
| Muse Glimmer 30B | | | |
GoodTime Greenhouse first choice named as an alternative argued againstblank: not namedEach cell is one answer, GoodTime on the left and Greenhouse on the right.The direct prompt
GoodTime first, Greenhouse an alternative
3 of 14 modelsGreenhouse was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
8 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
3 of 14 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
GoodTime2%#7 of 16Greenhouse0%#13 of 16GoodTime12%#3 of 15Greenhouse4%#7 of 15GoodTime55%#1 of 13Greenhouse9%#4 of 13What the models said about GoodTime
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to Avoid - Enterprise-focused tools like GoodTime, VidCruiter, or Paradox” Kimi K2 · budget prompt · hard negative
“Avoid these for budgets: Tools like GoodTime, Ashby, Paradox, or ModernLoop” Grok 4.20 · budget prompt · hard negative
“Avoid GoodTime (unless you're enterprise and test heavily)” DeepSeek V4 Flash · negative prompt · hard negative
“If you already have an ATS (like Greenhouse/Lever): Add GoodTime. It saves hiring managers significantly more time than Calendly” Qwen 3.7 Flash · paraphrase prompt · first choice
“GoodTime for most mid-market B2B teams that take hiring seriously and want a scalable recruiting workflow.” GPT-5.4 mini · direct prompt · first choice
“Highly rated for mid-market and enterprise use, especially for structured, multi-stage hiring processes” Mistral Small · direct prompt · first choice
What the models said about Greenhouse
No label in this category carried a quote.
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.