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Index › Customer › In-app messaging › Intercom vs CometChat
In-app messaging and customer communications · October 2026 Edition

Intercom vs CometChat

Five of fourteen models named Intercom first on the direct prompt; zero named CometChat. Intercom was named by thirteen of the fourteen models and CometChat by nine and Intercom carries 47 labels and CometChat 16, so the shares are not directly comparable.

Intercom

accepted challenger

United States, founded 2011. Named in twelve categories this edition.

CometChat

accepted challenger

Named in one category this edition.

First-choice share21%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate17%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#8A position in a field of 15; printed, not drawn.
Labels4716A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Intercom reading right to left. Rank and label count are printed, not drawn.Appcues was named alongside these two in eleven of the fourteen direct answers. Intercom vs OneSignal · Intercom vs Userpilot · Intercom vs Appcues

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 in-app messaging and customer communications page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
IntercomFirst choices, of fourteen modelsCometChat
Direct50
Paraphrase601 against Intercom
Comparative31
Budget-constrained013 against Intercom
Scale-constrained10
Negative004 against Intercom · 1 against CometChat
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 Intercom and CometChat stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Intercom CometChat first choice named as an alternative argued againstblank: not namedEach cell is one answer, Intercom on the left and CometChat on the right.

The direct prompt

The plain question, one answer per model, grouped by where Intercom and CometChat stood in it.

Intercom first, CometChat an alternative

5 of 14 modelsCometChat was named in the answer but not as the choice, or not at all.
GPT-5.4 miniIntercom alternatives: Appcues, Pendo
Gemini 3.5 FlashIntercom, Userpilot alternatives: Appcues, Front, Plain, Pylon, Userflow
Grok 4.1 FastIntercom alternatives: CometChat, LiveChat, Sendbird, Zendesk
DeepSeek V4 FlashIntercom alternatives: Appcues, OneSignal, Userpilot
GLM 4.7 FlashXIntercom alternatives: Appcues, CleverTap, Userpilot

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5no first choice alternatives: Front, Gleap, Helply, Intercom, Product Fruits
Kimi K2Appcues, Userpilot alternatives: Chameleon, Intercom
MiniMax M2.5Userpilot alternatives: Appcues, Chameleon, Intercom
GPT-6 LunaUserpilot alternatives: Appcues, Intercom, Pendo
Muse Glimmer 30BAppcues, Userpilot alternatives: Braze, Intercom, Pendo, Product Fruits

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarAppcues alternatives: Knock, OneSignal
Mistral SmallKnock alternatives: Appcues, OneSignal
Llama 4 MaverickKnock, Respond.io
Qwen 3.7 FlashAppcues alternatives: Chameleon, Pendo, UserGuiding, Userpilot

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
Intercom leads by twenty points.
Intercom22%#1 of 13
CometChat2%#8 of 13
The full small business standing →
Mid-marketThe figures above
Intercom leads by nineteen points.
Intercom21%#1 of 15
CometChat2%#8 of 15
The full mid-market standing →
Enterprise
Intercom leads by six points.
Intercom9%#3 of 16
CometChat4%#5 of 16
The full enterprise standing →

What the models said about Intercom

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“What I'd Avoid for Mid-Market B2B: - Intercom: Pricing tied to MAUs/contacts scales unpredictably” Kimi K2 · paraphrase prompt · hard negative
“Intercom is notorious for pricing startups out with seat-based and volume-based AI pricing” Gemini 3.5 Flash · budget prompt · hard negative
“Intercom (The Gold Standard for In-App Chat) ... It remains the absolute best conversational tool for B2B SaaS, despite its premium price tag.” Gemini 3.5 Flash · direct prompt · first choice

What the models said about CometChat

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“CometChat, for instance, has a steep jump from its free tier (limited to 100 users) to a minimum paid tier of around $299/month” Gemini 3.5 Flash · negative prompt · soft negative
“For user-to-user chat integration (MVP): Go with CometChat.” Gemini 3.5 Flash · budget prompt · first choice
“→ Sendbird, Stream, or CometChat” DeepSeek V4 Flash · comparative prompt · first choice
“Their "Builder" plan is free forever for development/testing and includes up to 100 users with full features.” Qwen 3.7 Flash · budget prompt · alternative
Also compared

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.