IT documentation · November 2026 Edition
Freshservice vs IT Glue
Zero of fourteen models named Freshservice first on the direct prompt; zero named IT Glue. Freshservice was named by twelve of the fourteen models and IT Glue by fourteen and Freshservice carries 18 labels and IT Glue 56, so the shares are not directly comparable.
Named in ten categories this edition.
Named in two categories this edition.
First-choice share9%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%34%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#5A position in a field of 15; printed, not drawn.
Labels1856A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Freshservice reading right to left. Rank and label count are printed, not drawn.Confluence was named alongside these two in fourteen of the fourteen direct answers. Hudu vs Freshservice · Hudu vs IT Glue · Confluence vs Freshservice
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 IT documentation page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
FreshserviceFirst choices, of fourteen modelsIT Glue
Direct003 against IT Glue
Paraphrase542 against IT Glue
Comparative04
Budget-constrained004 against IT Glue
Scale-constrained01
Negative0010 against IT Glue
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Freshservice and IT Glue stood in it.
| 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 | | | | |
Freshservice IT Glue first choice named as an alternative argued againstblank: not namedEach cell is one answer, Freshservice on the left and IT Glue on the right.The direct prompt
The plain question, one answer per model, grouped by where Freshservice and IT Glue stood in it.
Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniConfluence alternatives: Document360, Guru, IT Glue
Gemini 3.5 FlashHudu alternatives: Confluence, Document360, GitBook, IT Glue, Scribe, Tango
Perplexity SonarHudu alternatives: Confluence, Document360, Freshservice, SharePoint
Grok 4.20Confluence alternatives: GitBook, Hudu, IT Glue, Notion
Mistral SmallConfluence, Document360 alternatives: Freshservice, GitBook, IT Glue, Mintlify
Llama 4 MaverickConfluence alternatives: Document360, Freshservice, GitBook
MiniMax M2.5Document360 alternatives: Confluence, Freshservice, GitBook, Hudu
GPT-6 LunaHudu alternatives: Confluence, IT Glue, SharePoint
Muse Glimmer 30BConfluence alternatives: Document360, Freshservice, Notion
Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Confluence, Hudu alternatives: Document360, Tettra
DeepSeek V4 FlashConfluence, Hudu alternatives: Document360, Notion
Qwen 3.7 FlashHudu alternatives: Confluence, Guidde, Scribe
Kimi K2Confluence alternatives: Document360, Notion
GLM 4.7 FlashXDocument360 alternatives: Confluence, GitBook
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
IT Glue leads by eight points.
IT Glue8%#5 of 14Freshservice0%#– of 14Mid-marketThe figures above
Level: the same share of first choices.
Freshservice9%#4 of 15IT Glue9%#5 of 15Enterprise
What the models said about Freshservice
No label in this category carried a quote.
What the models said about IT Glue
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Stagnant development and lack of meaningful updates in recent years; search functionality is often criticized as weak or unreliable; high pricing” Grok 4.20 · negative prompt · hard negative
“What to Avoid ... Designed for MSPs ... overpriced and over-engineered for internal IT” Kimi K2 · direct prompt · hard negative
“Avoid IT Glue or Hudu unless you are an MSP” Perplexity Sonar · budget prompt · hard negative
“Choose IT Glue for a mature MSP or internal IT team needing highly structured infrastructure documentation.” Perplexity Sonar · comparative prompt · first choice
“The most mature and widely adopted MSP documentation platform with the deepest PSA/RMM integration ecosystem.” DeepSeek V4 Flash · comparative prompt · first choice
“General ranking lists also put IT Glue first for IT documentation, followed by Confluence and Freshservice.” Muse Glimmer 30B · comparative prompt · first choice
Also compared
Hudu vs FreshserviceHudu vs IT GlueConfluence vs FreshserviceConfluence vs IT GlueBookStack vs FreshserviceBookStack vs IT GlueFreshservice vs Document360Freshservice vs NotionFreshservice vs ONES WikiIT Glue vs Document360IT Glue vs NotionIT Glue vs ONES WikiAll twenty-eight head-to-head pages and the full IT documentation standing
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.