Thirteen of fourteen models named Intercom Fin AI Agent first on the direct prompt; zero named Zendesk AI. Intercom Fin AI Agent was named by fourteen of the fourteen models and Zendesk AI by thirteen and Intercom Fin AI Agent carries 54 labels and Zendesk AI 40, so the shares are not directly comparable.
By Intercom, United States, founded 2011. Named in one category this edition.
By Zendesk, San Francisco, United States, founded 2007. 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 Chatbots and conversational AI for support page.
Across every category in the November 2026 Edition, Intercom Fin AI Agent and Zendesk AI were named in the same answer 101 times, of the 170 answers naming Intercom Fin AI Agent and the 111 naming Zendesk AI. In those answers Zendesk AI took the first choice ten times and Intercom Fin AI Agent thirty-eight.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Why to Avoid: This creates a "mystery bill." It is very difficult to forecast monthly costs” GLM 4.7 FlashX · negative prompt · hard negative
“underpowered SLAs, lightweight workflows, and the need to add tools or workarounds to handle core support processes—driving up costs and complexity” Muse Glimmer 30B · comparative prompt · soft negative
“Enterprise tools like Intercom (Fin) or Zendesk often charge per resolved ticket, which can escalate quickly.” Gemini 3.5 Flash · budget prompt · soft negative
“Intercom excels when you want fast deployment inside web or mobile apps. Fin, its AI layer, focuses on resolving issues before routing to humans.” Kimi K2 · comparative prompt · first choice
“Choose Intercom (Fin) if you want the best fast-to-deploy, modern, all-in-one conversational platform for modern B2B SaaS.” Gemini 3.5 Flash · direct prompt · first choice
“Intercom and Freshchat are the best all-around choices due to their ease of use, strong integrations, and scalability” Mistral Small · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Platforms with Notable Red Flags ... Zendesk - Issues: Ironically has "worst customer support" according to user reviews” Kimi K2 · negative prompt · hard negative
“However, it is expensive. The base "Suite Team" plan starts around $55/agent/month, and the AI features are often locked behind higher tiers.” GLM 4.7 FlashX · direct prompt · soft negative
“Legacy or overhyped AI add-ons (e.g., basic bots in older Zendesk or similar systems): Reviews often note they feel tacked-on” Grok 4.20 · negative prompt · soft negative
“Zendesk is the strongest all-around pick for established support teams, with pre-trained AI agents that work across email, chat, voice, and social.” Claude Haiku 4.5 · comparative prompt · first choice
“Intercom (with Fin AI) and Zendesk AI stand out as the overall top recommendations for mid-sized B2B companies” Gemini 3.5 Flash · paraphrase prompt · first choice
“established hubs like Zendesk, Intercom, or LiveChat are preferred for core customer support” Qwen 3.7 Flash · negative prompt · first choice
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.