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Index › GTM › Customer › Support chatbots › Tidio vs Freshchat
Chatbots and conversational AI for support · November 2026 Edition

Tidio vs Freshchat

Zero of fourteen models named Tidio first on the direct prompt; one named Freshchat. Tidio was named by fourteen of the fourteen models and Freshchat by eight and Tidio carries 35 labels and Freshchat 11, so the shares are not directly comparable.

Tidio

accepted challenger

founded 2013. Named in seven categories this edition.

Freshchat

accepted challenger

Named in three categories this edition.

First-choice share19%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#5A position in a field of 10; printed, not drawn.
Labels3511A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Tidio reading right to left. Rank and label count are printed, not drawn.Intercom Fin AI Agent was named alongside these two in fourteen of the fourteen direct answers. Intercom Fin AI Agent vs Tidio · Intercom Fin AI Agent vs Freshchat · Tidio vs Freshdesk

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 Chatbots and conversational AI for support page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
TidioFirst choices, of fourteen modelsFreshchat
Direct01
Paraphrase001 against Tidio
Comparative10
Budget-constrained90
Scale-constrained00
Negative001 against Tidio
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 Tidio and Freshchat stood in it.
ModelDirectFRParaphraseFRComparativeFRBudget-constrainedFRScale-constrainedFRNegativeFR
Claude Haiku 4.5
GPT-5.4 miniFR
Gemini 3.5 Flash
Perplexity SonarFR
Grok 4.20FR
Mistral SmallFR
DeepSeek V4 FlashFRFR
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashXFR
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30BFR
TidioFR Freshchat first choice named as an alternative argued againstblank: not namedEach cell is one answer, Tidio on the left and Freshchat on the right.

The direct prompt

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

Freshchat first, Tidio not the choice

1 of 14 modelsTidio was named in the answer but not as the choice, or not at all.
Mistral SmallFreshchat, Intercom Fin AI Agent alternatives: Botpress, Drift, Zendesk AI

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Perplexity SonarIntercom Fin AI Agent alternatives: Freshchat, Freshdesk, HubSpot Service Hub, TeamSupport, Zendesk AI
Grok 4.20Intercom Fin AI Agent alternatives: Freshchat, HubSpot Service Hub, Zendesk AI
DeepSeek V4 FlashIntercom Fin AI Agent alternatives: Freshchat, Freshdesk, TeamSupport, Zendesk AI
Llama 4 MaverickIntercom Fin AI Agent alternatives: Drift, TeamSupport, Tidio

Neither was named

9 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5TeamSupport alternatives: Freshdesk, Halo AI, Intercom Fin AI Agent
GPT-5.4 miniIntercom Fin AI Agent alternatives: Ada, Zendesk AI
Gemini 3.5 FlashIntercom Fin AI Agent alternatives: Ada, Plain, Pylon, Zendesk AI
Qwen 3.7 FlashIntercom Fin AI Agent alternatives: Kayako, Pylon, Salesforce Service Cloud, Zendesk AI
Kimi K2Intercom Fin AI Agent alternatives: Ada, Freshdesk, Zendesk AI
GLM 4.7 FlashXIntercom Fin AI Agent alternatives: Freshdesk
MiniMax M2.5Freshdesk, Intercom Fin AI Agent alternatives: TeamSupport
GPT-6 LunaIntercom Fin AI Agent alternatives: Agentforce for Service, HubSpot Service Hub, Zendesk AI
Muse Glimmer 30BIntercom Fin AI Agent alternatives: Ada CX, Fini, Pylon, Zendesk AI

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
Tidio leads by thirty points.
Tidio30%#1 of 11
Freshchat0%#– of 11
The full small business standing →
Mid-marketThe figures above
Tidio leads by seventeen points.
Tidio19%#2 of 10
Freshchat2%#5 of 10
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Tidio0%#– of 12
Freshchat0%#– of 12
The full enterprise standing →

What the models said about Tidio

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

“Low-cost, usage-based tools such as Tidio or Crisp: They can be suitable for small teams, but costs may rise with conversation volume or seats” Perplexity Sonar · negative prompt · soft negative
“Tidio stands out as one of the best customer support chatbot platforms for companies with a limited budget.” Grok 4.20 · budget prompt · first choice

What the models said about Freshchat

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

“Intercom and Freshchat are the best all-around choices” Mistral Small · direct prompt · first choice
“Best value-oriented option | Freshchat/Freshdesk | Balanced features for mid-sized teams” Perplexity Sonar · direct prompt · alternative
Also compared
Intercom Fin AI Agent vs TidioIntercom Fin AI Agent vs FreshchatTidio vs FreshdeskTidio vs Zendesk AIFreshdesk vs FreshchatZendesk AI vs FreshchatAll ten head-to-head pages and the full support chatbots 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.