Document360 vs Slite
Seven of fourteen models named Document360 first on the direct prompt; one named Slite. Document360 was named by fourteen of the fourteen models and Slite by twelve and Document360 carries 42 labels and Slite 26, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category 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 knowledge base and self-service page.
By framing
Document360First choices, of fourteen modelsSlite
Across every category in the October 2026 Edition, Document360 and Slite were named in the same answer forty-nine times, of the 114 answers naming Document360 and the 75 naming Slite. In those answers Slite took the first choice two times and Document360 five.
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 | | |||||
| GPT-6 Luna | | | | |||
| Muse Glimmer 30B | | | |
Document360 Slite first choice named as an alternative argued againstblank: not namedEach cell is one answer, Document360 on the left and Slite on the right.The direct prompt
Document360 first, Slite not the choice
7 of 14 modelsSlite was named in the answer but not as the choice, or not at all.Slite first, Document360 an alternative
1 of 14 modelsDocument360 was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.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
Document3604%#5 of 17Slite0%#10 of 17Document36017%#2 of 12Slite3%#6 of 12What the models said about Document360
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“these tend to be pricier or trial-based rather than truly budget-friendly” GPT-5.4 mini · budget prompt · soft negative
“Often cited as the best dedicated KB tool for mid-market B2B... Choose Document360 if you want a dedicated, professional knowledge base that scales well” Qwen 3.7 Flash · direct prompt · first choice
“Best Dedicated, Standalone Help Center: Document360 ... is the industry standard for mid-sized B2B companies.” Gemini 3.5 Flash · paraphrase prompt · first choice
“Highly rated for mid-market companies (25 to 500 people)... frequently cited as a top choice for B2B use cases.” Mistral Small · direct prompt · first choice
What the models said about Slite
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“one source flags it for no multilingual management, and another notes it is internal-only” Perplexity Sonar · negative prompt · soft negative
“lacks multilingual management, making it less suitable for teams with diverse language needs” Llama 4 Maverick · negative prompt · soft negative
“Slite: Ideal for AI-forward teams that need a single source of truth for humans and AI agents.” Llama 4 Maverick · scale prompt · first choice
“For a mid‑market B2B company, Slite is often the sweet spot” GLM 4.7 FlashX · direct prompt · first choice
“Great for internal wikis and team knowledge; less suited for customer-facing knowledge bases.” DeepSeek V4 Flash · direct prompt · alternative
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.