Knowledge base and self-service · September 2026 Edition
Freshdesk vs Helpjuice
Zero of twelve models named Freshdesk first on the direct prompt; one named Helpjuice. Freshdesk was named by eleven of the twelve models and Helpjuice by eight and Freshdesk carries 22 labels and Helpjuice 21, so the shares are not directly comparable.
By Freshworks, San Mateo. Named in five categories this edition.
Named in two categories this edition.
First-choice share12%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#8A position in a field of 16; printed, not drawn.
Labels2221A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Freshdesk reading right to left. Rank and label count are printed, not drawn.Document360 was named alongside these two in nine of the twelve direct answers. Notion vs Freshdesk · Notion vs Helpjuice · Document360 vs Freshdesk
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 knowledge base and self-service page.
By framing
How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
FreshdeskFirst choices, of twelve modelsHelpjuice
Direct01
Paraphrase61
Comparative00
Budget-constrained001 against Helpjuice
Scale-constrained00
Negative012 against Helpjuice
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 Freshdesk and Helpjuice 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 4.1 Fast | | | | |||
| Mistral Small | | | | | ||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | | ||||
| Qwen 3.7 Flash | | |||||
| Kimi K2 | | | ||||
| GLM 4.7 FlashX | | |||||
| MiniMax M2.5 | | | |
Freshdesk Helpjuice first choice named as an alternative argued againstblank: not namedEach cell is one answer, Freshdesk on the left and Helpjuice on the right.The direct prompt
The plain question, one answer per model, grouped by where Freshdesk and Helpjuice stood in it.
Helpjuice first, Freshdesk an alternative
1 of 12 modelsFreshdesk was named in the answer but not as the choice, or not at all.Llama 4 MaverickHelpjuice alternatives: Document360, Freshdesk, Pylon
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.Gemini 3.5 FlashDocument360, Guru alternatives: Confluence, Help Scout Docs, Helpjuice, Notion
Perplexity SonarDocument360 alternatives: Confluence, Helpjuice, Zendesk Guide
Grok 4.1 FastDocument360 alternatives: Confluence, Helpjuice, Notion, Slite, Zendesk Guide
Mistral SmallPlain alternatives: Confluence, Document360, Freshdesk, Guru, Slite
DeepSeek V4 FlashDocument360 alternatives: Freshdesk, Guru, Help Scout, Helpjuice, Zendesk
Kimi K2Confluence alternatives: Guru, Helpjuice, Notion, Slite, Zendesk Guide
MiniMax M2.5Document360 alternatives: Helpjuice, Zendesk Guide/Knowledge
Neither was named
4 of 12 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5no first choice alternatives: Bloomfire, Document360, Lore, Stonly, Zendesk Guide
GPT-5.4 miniZendesk alternatives: Confluence, Intercom
Qwen 3.7 FlashGuru, Intercom alternatives: Atlassian Confluence, Document360, Zendesk
GLM 4.7 FlashXHelply alternatives: Confluence, Notion, Plain, Slite
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
Freshdesk leads by twelve points.
Freshdesk12%#2 of 16Helpjuice0%#16 of 16Mid-marketThe figures above
Freshdesk leads by eight points.
Freshdesk12%#3 of 16Helpjuice4%#8 of 16Enterprise
The order flips: Helpjuice leads at enterprise.
Helpjuice19%#2 of 11Freshdesk0%#8 of 11What the models said about Freshdesk
No label in this category carried a quote.
What the models said about Helpjuice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“High-Risk Tools to Avoid ... Helpjuice ... Weak for customer-facing public help centers” Mistral Small · negative prompt · hard negative
“Steep pricing jumps between tiers (e.g., Helpjuice's $2,400/year jump for AI)” DeepSeek V4 Flash · negative prompt · soft negative
“Starting at: $120/month (up to 4 users) ... Cons: Monthly cost adds up” Mistral Small · budget prompt · soft negative
“I'd recommend Helpjuice if you want a dedicated, highly customizable, predictable-cost help center” DeepSeek V4 Flash · paraphrase prompt · first choice
“Helpjuice - Best for mid-market teams that want a fully managed, hand-customized knowledge base” Llama 4 Maverick · direct prompt · first choice
“Favor enterprise-grade like Document360 (audited versioning) or Helpjuice (governed theming)” Grok 4.1 Fast · negative prompt · first choice
Also compared
Notion vs FreshdeskNotion vs HelpjuiceDocument360 vs FreshdeskDocument360 vs HelpjuiceFreshdesk vs ConfluenceFreshdesk vs ZendeskFreshdesk vs BookStackFreshdesk vs GuruConfluence vs HelpjuiceZendesk vs HelpjuiceBookStack vs HelpjuiceGuru vs HelpjuiceAll twenty-eight head-to-head pages and the full knowledge base 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.